Don't use MongoDB
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I run engineering for foursquare. About a year and a half ago my colleagues and I and made the decision to migrate to MongoDB for our primary data store. Currently we have dozens of MongoDB instances across several different data clusters storing over a TB of data and handling 10s of thousands of requests per second (mostly reads but the write load is reasonably high as well).
Have we run into problems with MongoDB along the way? Yes, of course we have. It is a new technology and problems happen.
Have they been problematic enough to seriously threaten our data? No they have not.
Has Eliot and the rest of his staff @ 10Gen been extremely responsive and helpful whenever we run into problems? Yes, absolutely. Their level of support is amazing.
MongoDB is a complicated beast (as are most datastores). It makes tradeoffs that you need to understand when thinking about using it. It's not necessarily for everyone. But it most certainly can be used by serious companies building serious products. Foursquare is proof of that.
I'm happy to answer any questions about our experience that the HN community might have.
-harryh
Of course we've run into problems from time to time. No one goes from nothing to foursquare's level of success without running into some bumps along the way.
> were they serious? did someone lose money?
No.
> it would answer whether to use an eventually consistent db
MongoDB actually isn't really an eventually consistent datastore. It doesn't (for example) allow writes to multiple nodes across a network partition and then have a mechanism for resolving conflicts.
You had 11 hours downtime and didn't lose money?
What about opportunity cost? Reputation?
Now you have to share your secret :)
(I guess, if you weren't profitable, you had nothing to lose?)
Stockholm syndrome?
Or perhaps investor pressure to close ranks ;)
All databases perform poorly if you try to use them for use cases they don't fit, but I find with NoSQL databases it can be hard to find concise, objective statements of which use cases each is ideal for.
1) It is wrong to evaluate a system for bugs now fixed (but you can evaluate a software development process this way, however it is not the same as MongoDB itself, since the latter got fixed).
2) A few of the problems claimed are hard to verify, like subsystems crashing, but users can verify or deny this just looking at the mailing list if MongoDB has a mailing list like the Redis one that is ran by an external company (google) and people outside 10 gen have the ability to moderate messages. (For instance in Redis two guys from Citrusbytes can look/moderate messages, so even if I and Pieter would like to remove a message that is bad advertising we can't in a deterministic way).
3) New systems fails, especially if they are developed in the current NoSQL arena that is of course also full of interests about winning users ASAP (in other words to push new features fast is so important that perhaps sometimes stability will suffer). I can see this myself as even if my group at VMware is very focused on telling me to ship Redis as stable as possible as first rule, sometimes I get pressures about releasing new stuff ASAP from the user base itself.
IMHO it is a good idea if programmers learn to test very well the systems they are going to use with simulations for the intended use case. Never listen to the Hype, nor to detractors.
On the other side all this stories keep me motivated in being conservative in the development of Redis and try avoiding bloats and things I think will ultimately suck in the context of Redis (like VM and diskstore, two projects I abandoned).
One of the reasons I don't want to create a company around Redis, but want to stay with VMware forever as an employee developing Redis, is that I don't want development pressures that are not drive by: users, technical arguments. So that I can balance speed of development and stability as I (and the other developers) feel right.
Without direct reference to 10gen I guess this is harder when there is a product-focused company around the product (but I don't know how true this is for 10gen as I don't follow very closely the development and behavior of other NoSQL products).
On the other hand, commercial vendors like Oracle and open source projects like PostgreSQL recognize their role as database engineers is to first and foremost "do no harm." Ie, the database should never destroy data, period. Bugs that get released that do cause such things can be traced back to issues that are not related to a reckless pursuit of other priorities like performance. Watching the PostgreSQL engineers agonize over data integrity and correctness with any and all features that go out that are meant to improve performance is a re-assuring sight to behold.
This priority list goes without saying for professional database engineers. That there is such a 'tension' between stability and speed says less about a real phenomenon being debated by database engineers and more about the fact that many people who call themselves database engineers have about as much business doing so as so-called doctors who have not gone to medical school or taken the Hippocratic oath.
But I think a major difference between MySQL and Redis, MongoDB, Cassandra, and all the other NoSQL solutions out there is that MySQL had an impressive test bed: all the GPL LAMP applications, from forums to blogs, shipped and users by a shitload of users. We miss this "database gym" so these new databases are evolving in small companies or other more serious production environments, and this creates all the sort of problems if they are not stable enough in the first place.
So what you say can be more important for the new databases than it was for MySQL indeed.
And if MySQL never existed, what would have happened ? Would we have all used PostgreSQL in the first place and avoided years of painful instability ?
I read here all the time that fashion and ease of use are more attractive than reliability. And we introduce plenty of new software in complex architecture just because they are easy to use. We even introduce things like "eventual consistency", as if being eventually consistent was even an option for any business.
The problem is to not use random datastores. Use a database that has a proven record of stability. And if someone builds a database, he/she must prove that ACID rules are taken seriously, and not work around the CAP theorem with timestamps...
10 years ago, MySQL was not stable. PostgreSQL was. Today, most key-value databases are not stable, PostgreSQL is.
My sense was that it got a pretty thorough review and revision/rewrite in the transition from Postgres to PostgreSQL.
The change from Postgres to PostgreSQL was largely a UI/API change and the move from QUEL to SQL. However, over time virtually all of the software has been reviewed and rewritten. It's an excellent project, and I have been using it since 6.5.......
Most key-value databases didn't prove (as in: show me actual resistance tests, not supercompany123 uses it) that they are reliable. The day they do, I'll be the first one to use them. Until then, it's just a toy for devs who don't want to deal with ER models.
Then again, Postgres -- the project -- did not try to position itself (was there even such a thing as "positioning" for Postgres 16 years ago?) as a mature, stable project that one would credibly bet one's business on.
Lots of early database releases are going to be like Mongo, the question is how much the parties at play own up to the fact that their implementation is still immature and present that starkly real truth to their customers. So far, it seems commercial vendors are less likely to do that.
However, actually-not-a-terrible-idea is pretty relative, when you look at how the industry has evolved in the mean time. I mean, compared to MySQL at the time, PostgreSQL 6.5 was really not a terrible idea. 7.3 was the first release I didn't have to use MySQL as a prototyping system though.
And with 9.x things are getting even better.
I think you're missing the point a little. Yes, MySQL is a heap, and having to work with it in a Postgres world sucks. But, the point antirez is making in that comment (at least how I read into it) is that an active user community in ANY project is hugely important in that project's formation and "maturity" (sarcastically, of course, because Postgres is clearly more mature than MySQL). There's no extrapolation here to the top-level Mongo discussion going on in this thread -- I was just clarifying antirez's point.
I know benchmarks don't put this quite as fast as 5.5, but there are still possible gains to be made.
I would like to thank you for the great job you have and are doing on Redis. It's an awesome piece of technology and warms my heart as an European :). Are you based in Palermo ?
The fact that software engineers need to understand is that NoSQL is in no way a replacement for SQL in areas of data with inherent structure. In such areas, the relational model wins hands-down, and NoSQL is a big, heavy foot-gun. The caliber of the foot gun goes up significantly when multiple applications need to access the same data.
On the other hand, the relational model breaks down in some ways in many areas. Some things that you'd think are inherently structured (like world-wide street addresses) turn out to only be semi-structured. Document management, highly performing hierarchical directory stores, and a few other areas also are bad matches for the relational model. Other stores work well in many of these areas, from the filesystem to things like NoSQL databases.
The big problem occurs when semi-structured data (say files which contain printed invoice data in PDF format) have to be linked to inherently structured data (say, vendor invoices). In these cases, tradeoffs have to be made......
I have no doubt that NoSQL is able to find a niche. I doubt it will be one which at best involves inherently structured data.
What does that even mean? Is it some sort of cultural practice or religion we are afraid of losing. So we should look over lost data and bad designs just because something falls under the "NoSQL" category?
I think anyone married to a technology like it is a religion is poised for failure. Technology should be evaluated as a tool. "Is this tool useful to me for this job?" Yes/No? Not "it has NoSQL in its title, it must be good, I'll use that".
I disagree. A project's errata is a very good indicator for the overall quality of the code and the team. If a database-systems history is littered with deadlock, data-corruption and data-loss bugs up to the present day then that's telling a story.
2) A few of the problems claimed are hard to verify
The particular bugs mentioned in an anonymous pastie may be hard to verify. However, the number of elaborate horror-stories from independent sources adds up.
3) New systems fails, especially if they are developed in the current NoSQL arena
Bullshit. You, personally, are demonstrating the opposite with redis which is about the same age as MongoDB (~2 years).
When you strip MongoDB down to the parts that actually have a chance of working under load then you end up pretty close to a slow and unreliable version of redis.
Namely, Mongo demonstrably slows to a crawl when your working-set exceeds your available RAM. Thus both redis and mongo are to be considered in-memory databases whereas one of them is honest about it and the other not so much.
Likewise Mongo's advanced data structures demonstrably break down under load unless you craft your access pattern very carefully; i.e. growing records is a nono, atomic updates (transactions) are a huge headache, writes starve reads by design, the map-reduce impl halts the world, indexing halts the world, etc. etc.
My argument is that the feature disparity between mongo and redis stems mostly from the fact that Antirez has better judgement over what can be made work reliably and what can not. This is why redis clearly states its scope and limits on the tin and performs like a swiss watch within those bounds.
Mongo on the other hand promises the world and then degrades into a pile of rubble once you cross one of the various undocumented and poorly understood thresholds.
Thanks for that explanation. I agree that Mongo seems to have over-promised and under-delivered and that you do have to really craft your access pattern. I'm not a heavy MongoDB user, but from reading the docs and playing around, I was already under the impression that the performance of MongoDB is entirely up to me and that I would need a lot of understanding to get the beast working well at scale.
So, it's a tough call for me to say whether they over-promised or not, but like I said...I'm not a heavy user. I just read a lot. I do think it is easy to be deceived by Mongo's apparent simplicity (ie - usage of JSON, Javascript, schema-lessness, etc).
EDIT: zzzeek made a good point below about spending time in a low-key mode before really selling the huge feature-set, which convinced me, so I think you're right. I do like the idea of Mongo though, so hopefully they can get through it.
Apparently you have no idea how many critical bugs have been fixed in Redis...
Great point. It would also help if the company that makes a DB would put flashing banner on their page to explain the trade-offs in their product. Such as "we don't have single server durability built in as a default".
I understand if they are selling dietary supplements and are touting how users will acquire magic properties for trying the product for 5 easy payments of $29.99. In other words I expect shady bogus claims there. But these people are marketing software, not to end users, but to other developers. A little honesty, won't hurt. It is not bad that they had durability turned off. It is just a choice, and it is fine. What is not fine is not making that clear on the front page.
Anyone with half a brain can go look at the MongoDB codebase and deduce that it's amateur hour.
It's start up quality code but it's supposed to keep your data safe. That's pretty much the issue here -- "cultural problems" is just another way of saying the same thing.
Compare the code base of something like PostgreSQL to Mongo, and you'll see how a real database should be coded. Even MySQL looks like it's written by the world's best programmers compared to Mongo.
I'm not trying to hate on Mongo or their programmers here, but you've basically paid the price for falling for HN hype.
Most RDBMSes have been around for 10+ years, so it's going to take a long, long time for Mongo to catch up in quality. But it won't, because once you start removing the write lock and all the other easy wins, you're going to hit the same problems that people solved 30 years ago, and your request rates are going to fall to memory/spindle speed.
Nothing's free.
So even if in 30 years it's got the same characteristics as our current dominant data storage models I consider it a net win that I will be able to use a document oriented database for development over a more traditional RDBMS for some off my applications.
The richer our toolset is the better we are off as not every problems is a nail to be hammered in with an RDBMS.
So a high five to all the people who dare go against convention and take a chance on a new approach to data modeling being it Mongo, Riak, CouchDb, Redis, Neo4j, Cassandra, HBase or any other awesome opensource project out there.
Document databases, network databases and hierarchical databases (IMS, CODASYL etc) predate relational databases by decades.
Relational is the universal default for a simple reason. When first introduced it proved to be far better, in every conceivable way, than the technologies it replaced.
It's as simple as that. Relational is a slam-dunk, no-brainer for 99.99% of use cases.
Still, if you really want a fast, proven system for one of the older models, you can get IBM to host stuff for you on a z/OS or z/TPF instance, running IMS. It'll have more predictable performance than AWS to boot.
BTW if you want nosql-style schema flexibility within an RDBMS, then a simple solution is to store XML or JSON in in a character blob. Keep the fields you need to search over in separate indexed fields. If you make incompatible version changes, then add a new json/xml field.
In all sincerity, I would strongly recommend against this. If your problem absolutely defies normalisation, don't use a relational database.
The relational model is ideal in many circumstances. However, it breaks down in semi-structured content, content where---parentheses for grouping---(hierarchical structure is important, data is seldom written and frequently read, and where read performance navigating the hierarchy is most important) and so forth.
So I'd generally agree, but not every problem is in fact a nail.
Again, this problem is not new. Database greybeards call this OLAP and it's been around since the 80s.
There is nothing new under the sun in this trade.
OLAP is typically used to refer to environments which provide complex reports quickly across huge datasets, so a lot of materialized views, summary tables, and the like may be used (as well as CUBEs and the like). Hierarchical directories are different. In a relational model you have to transfers the hierarchy to get the single record you want and you are not aggregating like you typically do in an OnLine Analytical Processing environment.
This is why OpenLDAP with a PostgreSQL backend sucks, while OpenLDAP with a non-relational backend (say BDB) does ok.
I am not saying anything new is under the sun, just that some of the old structures haven't gone away.
That's why OLAP came along. Structured denormalisation, usually into star schemata, that provide fast ad-hoc querying. I think part of the enthusiasm for NoSQL arises because most university courses and introductory database books will go into normalisation in great detail, but OLAP might only get name checked. So folk can get an incomplete impression of what relational systems can do.
If I had a purely K/V data problem -- a cache, for example -- I would turn to a pure K/V toolset. Memcache, for example.
Hierarchical datasets have long been the blindside for relational systems. Representable, but usually requiring fiddly schemes. But in the last decade SQL has gotten recursive queries, so it's not as big a problem as it used to be.
As far as recursive queries, I am not 100% sure this is ideal either from a read performance perspective. There are times when recursive queries are helpful from a performance perspective, but I don't see a good way to index, for example, path to a node. Certainly most databases don't do this well enough to be ideal for hierarchical directories. For example indexing the path to a node might be problematic, and I am not even sure you could do this reliably in PostgreSQL because the function involved is not immutable.
> However, because there is no way to set constraints across joins, in practice, the dependencies of data constraints are as important as the dependencies of data values.
I don't follow your argument here. Could you restate it?
> As far as recursive queries, I am not 100% sure this is ideal either from a read performance perspective. There are times when recursive queries are helpful from a performance perspective, but I don't see a good way to index, for example, path to a node.
Poking around the Oracle documentation and Ask Tom articles, it seems to be more art than science; mostly based on creating compound indices over the relevant fields. Oracle is smart enough to use an index if it's there for a recursive field, but will struggle unless there's a compound index for other fields. I don't see an obvious way to create what you might call 'recursive indices', short of having an MV.
> Certainly most databases don't do this well enough to be ideal for hierarchical directories.
It'll never perform as well as a specialised system. But relational never will. An RDBMS won't outperform a K/V store on K/V problems, won't outperform a file system for blob handling and so on. This is just another example of the No Free Lunch theorem in action.
My contention is that we, as a profession of people who Like Cool Things, tend to discount the value of ACID early and then painfully rediscover its value later on. The business value of ACID is not revealable in a benchmark, so nobody writes breathless blog posts where DrongoDB is 10,000x more atomic than MetaspasmCache.
Sure.
Quick note, will use PostgreSQL SQL for this post.
Ok, take a simple example regarding US street addresses.
A street address contains the following important portions:
1) Street address designation (may or may not start with a digit). We will call this 'address' for relational purposes. 2) City 3) State 4) Zipcode
As for data value dependencies:
zipcode is functionally dependent on (city, state), and so for normalization purposes we might create two relations, assuming this is all the data we ever intend to store (which of course is always a bad assumption):
create table zipcode(zipcode varchar(10) not null primary key, city text not null, state text not null, id serial not null unique);
create table street( id serial not null, address text, zipcode_id int references zipcode(id), primary key(address, zipcode_id));
So far this works fine. However, suppose I need to place an additional constraint on (address) for some subset of (zipcodes), let's say all those in New York City. I can't do it declaratively, because all data constraints must be internal to a relation.
So at that point I have two options:
1) You can write a function which determines whether a zipcode_id matches the constraint and check on that, or
2) You can denormalize your schema and add the constraint declaratively.
I did some searching and determined strangely that although subqueries in check constraints are part of SQL92, the only "database" that seems to support them is MS Access. But while there are obvious issues regarding performance, I don't see why these couldn't be solved using indexes the same way foreign keys are typically addressed.
> Poking around the Oracle documentation and Ask Tom articles, it seems to be more art than science; mostly based on creating compound indices over the relevant fields. Oracle is smart enough to use an index if it's there for a recursive field, but will struggle unless there's a compound index for other fields. I don't see an obvious way to create what you might call 'recursive indices', short of having an MV.
No, there is an inherent problem here. Your index depends on other data in the database to be accurate. You can create an index over parent, etc. but you still end up having to check the hierarchy all the way down to find the path. You can't just index the path.
Consider this:
CREATE TABLE treetest (id int, parent int references treetest(id));
INSERT INTO treetest (id, parent) values (1, null), (2, 1), (3, 1), (4, 1), (5, 2), (6, 2), (7, 6);
The path to 7 is: 1,2,6,7. To find this, I have to hit 4 records in a recursive query. That means 4 scans.
So suppose we index this value, reducing this to one scan.
Then suppose we: update treetest set parent = 3 where id = 6;
and now our index doesn't match the actual path anymore.
With specialized hierachical databases, you could keep such paths indexed and make sure they are updated when any node in the path changes. There isn't a good way to do this in relational systems though because it is outside the concept of a relational index.
> My contention is that we, as a profession of people who Like Cool Things, tend to discount the value of ACID early and then painfully rediscover its value later on. The business value of ACID is not revealable in a benchmark, so nobody writes breathless blog posts where DrongoDB is 10,000x more atomic than MetaspasmCache.
No doubt about that. I think we are 100% in agreement there!
I'd also add that while RDBMS's aren't really optimal as backings for something like LDAP for a big directory, and while RDBMS's are horribly abused by dev's who don't understand them (ORM's and the like), they really are amazing, valuable tools, which are rarely valued enough or used to their fullest.
Later this week, I expect to write a bit of a blog post on http://ledgersmbdev.blogspot.com on why the intelligent database model (for RDBMS's) is usually the right model for the development of many business applications.
> 1) You can write a function which determines whether a zipcode_id matches the constraint and check on that, or
Ah, this old chestnut. Been there, written the PL/SQL trigger, got the t-shirt. Agreed that there isn't a purely declarative approach here.
> You can't just index the path.
Postgres might be the winner here, if someone sufficiently motivated came along and wrote a custom index type for this use case.
Consequently I don't believe there is a reasonable way to index this because there is no way to ensure the indexes are current and so you don't have a good way of testing that a row is in a path on the tree other than building the tree with recursive subqueries.
The thing is, unless you have a system which is aware of hierarchical relationships between the rows (which by definition is outside the relational model), you have no way of handling this gracefully. So here you have lots of reads, I really think dedicated hierarchical systems will win for hierarchical data.
Of course this wouldn't necessarily mean you couldn't store everything in the RDBMS and periodically export it to the hierarchical store.....
You're better off with MySQL or PostgreSQL managing a key-value table where the value is a blob of JSON (or XML, which I've done in the past), then defining a custom index, which is pretty damn easy in PostgreSQL. Then you have hundreds of genius-years of effort keeping everything stable, and you still get NoSQL's benefits. Everybody wins.
That's not exactly true; what they did was offer a generic query and constraint model that worked well in all cases while offering reasonable performance. They were not generally faster in optimal cases, but they were much easier to query especially given new requirements after the fact because the queries weren't baked into the data model itself. That generic query ability and general data model always come at the cost of speed; always. Document databases have always been faster in the optimal use case.
Take a look at for example: bool BtreeBucket<V>::find
Without even thinking about what it is doing, it's quite clear that it is not readable code, and it's not immediately obvious what the high level structure of the logic is. The function does not even fit into two screens so it's hard to reason about; your short-time memory is overused.
if there is a part of mongodb that I am sure does not contain bugs, it is that very file you link to.
if you want to know what it does, go out and read the relevant papers on data base technology. or graduate in CS.
I also know that an 85-line, 7-argument method in a 1988-line file shouldn't depend on a global variable ("guessIncreasing") modified from several other, unrelated functions. I know that in bt_insert, which (apparently) assigns to "guessIncreasing" and then resets it to false just prior to exit, should be using an RAII class to do so instead of trying to catch every exit path, especially in a codebase that uses exceptions.
This code is amateur hour.
I found the btree file relatively readable. Some macro stuff is not familiar to me, but I am sure I could figure it out in a few hours if I felt like. And I haven't yet rolled around to implementing a full-on btree, ever.
I was also turned off by the sloppy use of memory. Heap allocated objects returned from functions with poor checks to see if anyone manages that memory on the other side. Lots of instances of strcmp, strcpy and similar unsafe string/buffer manipulation functions.
It's been a while since I looked at it so I don't have any particular examples at hand, but that was my impression.
Do you care to provide some examples for those not familar with proper C++/Boost development practices, please?
The bug was only triggered when the delayed_commits option was on (holds off on fsyncing when lots of write operations are coming in) and there was both a write conflict and a period of inactivity - when the database was shut down, any writes that happened afterwards would not be saved.
They immediately worked to develop a process that would prevent any data from being lost if you didn't shut down the server, then a week later had released an emergency bugfix version without the bug. Then later they released a tool that could recover any data lost from the bug if the database hadn't been compacted.
That's the kind of attitude database developers need to have towards data integrity.
Couch may have its warts, but it is damn reliable.
I mean, how hard can it be to
1) Manage some indexes,
2) Keep some metadata around and
3) Build some half-assed single index query planner?
Couch is already a solid piece of technology. It just needs a better API to "sit" on top of it, kinda like what Membase is doing now.
edit: or on top of Riak, Cassandra, PostgreSQL or etc ... on the API side, Mongo has clearly won.
Why are't links to 10gen's Jira provided? Where's the test code that shows the problems they had with the write lock?
This is an extremely shallow analysis.
I don't agree with a lot of his conclusions, but mostly his data is correct.
1 - Default writes are unsafe by default:
MongoDB supports a number of "write concerns":
* fire-and-forget or "unsafe"
* safe mode (only written to memory, but the data is checked for "correctness", like unique constraint violations)
* journal commit
* data-file commit
* replicate to N nodes
The last 4 can be mixed and matched. Most (all?) drivers allow this to be specified on a per-write basis. It's an incredible amount of flexibility. I don't know of any other store that lets you do that.
When a user registers, we do a journal commit ({j:true}), 'cuz you don't want to mess that up. When a user submits a score, we do a fire-and-forget, because, if we lose a few scores during the 100ms period between journal commit, it isn't the end of the world (for us, if it is for you, always use j:true)
The complaint is the default-behavior (which I think you can globally configure in most drivers) of the driver? Issue a pull request. Is the default table created in MySQL still MyISAM ?
2 and 6 - Lost Data
This is the most damning point. But what can I say? "No?" My word versus his? I haven't seen those issues in production, I hang out in their google groups and I don't recall seeing anyone bring that up - though I do tend to avoid anything complicated/serious and let the 10gens guys handle that. Maybe they did something wrong? Maybe they were running a development release? Maybe they did hit a really nasty MongoDB bug.
3 - Global Lock
MongoDB works best if your working set fits in memory. That should simply be an operation goal. Beyond that, three points. First, the global lock will yield, i believe (someone more informed can verify this). Second, the story gets better with every version and it's clearly high on 10gen's list.
Most importantly though, it's a constraint of the system. All systems have constraints. You need to test it out for your use-case. For a lot of people, the global lock isn't an issue, and MongoDB's performance tends to be higher than a lot of other systems. Yes it's a fact, but with respect to "don't use MongoDB", its FUD. It's an implementation detail, that you should be aware of, but it's the impact of that implementation details, if any, that we should be talking about.
3 and 4 - Sharding
Sharding is easy, rebalancing shards is hard. Sharding is something else which got better in 1.8 and 2.0, which the author thinks we ought to simply dismiss. I don't have enough experience with MongoDB shard management to comment more. I think the foursquare outage is somewhat relevant though (again, keeping in mind that things have improved a lot since then).
7 - "Things were shipped that should have never been shipped"
This is a good verifiable point? I remember using MySQL cluster when it first shipped. That was a disaster. I also remember using MySQL from a .NET project and opened up a good 3-4 separate bugs about concurrency issues where you could easily deadlock a thread trying to pull a connection from the connection pool.
I once had to use use clearcase. Talk about something that shouldn't have shipped.
This is essentially an attack on 10gen, that ISN'T verifiable. Again, it's his anonymous word versus no ones. Just talking about it is giving it unjust attention.
8 - Replication
It's unclear if this is replica sets or the older master-slave replication. Either way, again, I don't think this is verifiable. In fact, I can say that, relatively speaking, I see very few replica set questions in the groups. It works for me, but I have a very small data set, my data pieces themselves are small. Obviously some people are managing just fine (I'm not going to go through their who's who, I think we all know some of the big MongoDB installations).
9 - The "real" problem
We've all seen some pretty horrible things. I was using MySQL in 5.0 and there was some amazing bugs. There's a bug, which I think still exists, where SQL Server can return you the incorrect inserted id (no, not using @@identify, using scope_identity) when you use a multi-core system. MS spent years trying to fix it.
I guess I can say what 10gen never could...If you were using MongoDB prior to 1.8 on a single server, it's your own fault if you lost data. To me, replication as a means to provide durability never seemed crazy. It just means that you have to understand what's going on.
Look, I don't doubt that this guy really ran into problems. I just think they have a large data set with a heavy workload, they thought MongoDB was a silver bullet, and rather than being accountable for not doing proper testing, they want to try and burn 10gen.
They didn't act responsibly, and now they aren't being accountable.
You can STILL deadlock a transaction against itself in MySQL w/Innodb. How do they let this happen? I do not know. I just know I have been bitten by deadlocks in multi-row inserts quite often there enough to get really really frustrated when I use that db. This is in fact documented in the MySQL manual.
For better or worse, projects which start out without a goal to offer highly reliable software from the start never seem to be able to offer it later.
You could say "don't use SQL Server"..or you could say "it's important that you understand SQL Server's locking behavior"
I have NEVER had issues with PostgreSQL transactions deadlocking against themselves, even with monstrous stored procedures.
edit:
I brought up MySQL because I think we all know that companies, you, me knowingly ship products with bug. In fact, you can look at public bug tracking for a bunch of major software and see bug fixes scheduled for future releases.
However, if you are going to accuse a database vendor of knowingly shipping data-corruption bugs, I think you absolutely have to back that up. It's slanderous. Obviously, if you think that, you also shouldn't use their product. But you either know something the rest of us don't, or you're a complete ass, if you make those kinds of statements without evidence.
I didn't comment on the rest because I don't care, not because I don't get it.
Well, except for that thing where the replication decided that the empty set was the most recent and blew everything else away. And those cases where keys went away.
Losing data, particularly when the server goes down, is fine. Even not writing data isn't terrible, though his points about not knowing whether it has been written in case of failure are really good ones. But corrupting data and then replicating that corrupted data is really, really bad. Often unfixably bad.
They didn't act responsibly, and now they aren't being accountable.
For the complaints about the default write stuff, sure. For everything else... Dunno. He brought up a lot of real, actual issues which were not documented MongoDB behavior. Yes, there's also a fair bit of complaining about the documented bits, and sure, boo-hoo, whatever. But the idea that 10gen is shipping stuff with serious data integrity bugs, and doing so knowing, doesn't seem out of line here.
And while MySQL also has some bad stuff, sure, it has nothing like as many data integrity bugs as MongoDB.
And I say all of this as a serious fan of MongoDB.
Refutations are going to fall into two categories, it seems:
1. Questioning my honesty
2. Questioning my competence
Re #1, I'm not sure what you imagine my incentive to lie might be. I honestly just intended this to benefit the community, nothing more. I'm genuinely troubled that it might cause some problems for 10gen, b/c, again, Eliot & co are nice people.
Re #2, all I can do is attempt to reassure you we're generally smart and capable fellows. For example, these same systems exhibit none of these problems, and we're sleeping quite well through the night, on the new database system they've moved to. I'll omit the name of the database system just so there is no conflict that might undermine my integrity and motives (see #1).
edit:
(also, there are a few comments about "someone unknown/new around here"... trust me, I'm not new or unknown. I'm a regular.)
Those two things are connected: I can't provide the evidence without revealing identity. And the reason for the anonymity is we still have some small databases with 10gen and a current support contract. I had intended to go public with all this after we had transitioned off the system entirely, but more and more reports have continued to pop up of people having trouble with MongoDB, and it seemed as though delaying would be imprudent. An anonymous warning would be more valuable than saying nothing.
So--if you choose to ignore or dismiss our claims, you're entitled. :-) I still feel satisfied that I did what I needed to do.
- Who are you?
Your HN acct was created 14 hours ago, and it's name is extremely specific to this particular post -- "nomoremongo". Nothing wrong with it, just a little peculiar considering the subject mater.
- Where did you experience these problems?
I guess I could see some issue around revealing where you work, but honestly, that just sucks. It really doesn't have anything to do with questioning your honesty and integrity; it's more about just being open about things. If you're going to be open about your experiences, why not be open about all of it?
Not to be rude, but the anonymous-nature of this post comes off as a bit over-dramatic.
I presume that anyone would post such content anonymously.
If intellectual laziness like that is any indication, I doubt anyone is going to be reassured on your point #2. You've dropped a bomb on 10gen here, and done it anonymously to boot. You've got their people sifting through past issues on a Sunday, and for what? Because you fucked up a project by making poor choices, and probably took the well-deserved heat for it? Nevermind your categories. Man up and respond to these people directly, or don't respond at all.
Has anyone commenting ever used a piece of software that caused them major problems, while watching others with less experience talk about how great it is? For me, it is beyond my capabilities to refrain from speaking up about it.
His identity does not matter, and it would start a war between people or companies. He is not interested in doing that, and he is not speaking on behalf of a company. There is not really any other way to do it.
Sometimes people need to put information out there but don't want to be personally associated with the information. This is fairly logical, because they are not associated with the information. They just discovered what was already true.
Regarding the point of using getLastError(), the author is completely correct. But the problem is not so much that MongoDB isn't good, it's that developers start using it and expect it to behave like a relational DB. Start thinking in an asynchronous programming paradigm, and you'll have less problems.
I got bit my MongoDB early on. When my server crashed, I learned real quickly what fsync, journaling, and friends can do. The best thing a dev can do before using MongoDB is to RTFM and understand its implications.
The #1 reason that I used MongoDB, was because of the schema-less models. That's it. Early on in an applications life-cycle, the data model changes so frequently that I find migrations painful and unnecessary.
My two cents, hopefully it helps.
As long as your code can handle all versions of objects in current use, you can deploy new code, then either migrate objects as they're updated/rewritten, and/or slowly migrate objects in the background.
For certain types of schema changes in large enough data stores, this can be a killer feature. I remember one RDBMS setup I had to deal with where we were "stuck" having to do a lot of suboptimal schema changes because the changes we actually wanted to do resulted (based on tests in our dev environment) the system to slow to a crawl where it was unusable for 8+ hours and we just couldn't afford that kind of downtime. We spent a lot of engineering time working our way around something that'd simply be a non-issue in a schema-less system.
key, value
and then proceed to pay the cost of joins against it. Most of my excitement around NoSql comes from hard earned pain not from "oh new shiny thing, I got to use it".
Joins are no fun, yes, but as you gritted your teeth and implemented those cute little table-based key-value stores, did you find yourself mentally calculating the time required to restore the whole system from backup while muttering tiny prayers? Probably not. Did your code wake up the ops team an average of once per month for several years? Did you lose data? Did you have to put up an apologetic blog post? Did anyone have to get on the phone and rescue customer accounts, one at a time, with profuse apologies and gifts? (Now that is a non-scalable process...)
But at least this argument about maintenance is a real argument. The one about wanting to save time during initial development by skipping the declaration of schemas reads like the punchline of a Dilbert cartoon that you'd find taped to the wall in the devops lunchroom.
Slow interconnect between servers caused me headaches in the past with mysql for replication. Shared switched did the same. Problems with locks under high contention did the same. Problems with the client libraries the same. In fact all storage systems have similar problems and pain. Some are just more battle tested than others.
In my view, schemaless models are only desirable if the schema is not known until runtime, e.g. user specified fields or message structures, external file formats that you don't control but might need to query, etc.
There are many shortcomings of this approach but when dealing with highly unstructured data (or basically where the inherent structure is that of key/value pairs) it strikes me as the correct approach, and not different really from using NoSQL, XML, or any other non-relational store.
It's not as awful as it sounds, performance-wise. It is as awful as it sounds in terms of maintainability, of course.
it's always MySQL's fault in these things.
postgres=CREATE TABLE alter_benchmark(id bigint);
CREATE TABLE
postgres=# explain analyze
postgres-# insert into alter_benchmark (id) select * from generate_series(1, 200000000);
postgres=# create temporary table alter_benchmark(id bigint); CREATE TABLE postgres=# explain analyze insert into alter_benchmark (id) select * from generate_series(1, 200000000); QUERY PLAN
-------------------------------------------------------------------------------- ---------------------------------------------------------
Insert (cost=0.00..12.50 rows=1000 width=4) (actual time=1082180.877..1082180. 877 rows=0 loops=1)
-> Function Scan on generate_series (cost=0.00..12.50 rows=1000 width=4) (apostgres=# alter table alter_benchmark add test text;
ALTER TABLE
takes insignificant time (less than a second).
I feel so spoiled using PostgreSQL :-D
As I understand it PostgreSQL doesn't rewrite the table to change the column. It might to change the data type of a column. EXPLAIN ANALYZE doesn't work with ALTER TABLE because there is no query plan generated, so I have no idea how quickly the statement actually executed. All I know is it completed in under a second.
On short folks build their db around the ORM instead of vice versa.
I've been using Hibernate for 9 years and I finally came to the conclusion that it's just not worth the pain. When working on RDBMS I'm using straight SQL from now on.
I second that: schema-less is misunderstood.
There's a difference between flexibility of schema definition and flexibility of schema change[1].
Flexibility of schema change, which NoSQL does not solve, is increasingly more important. Not just for large data stores but also for the data development process and release process. To avoid playing the suboptimal schema-change game both the code and the data need to be updated together. Or at least be given the illusion that they have[2].
A probably obvious question most developers must have asked by now is: if we've built great tools to version source changes, how come we haven't built great tools to version data changes?
[1] - http://chronicdb.com/blogs/nosql_is_technologically_inferior...
I disagree. The most frequent use-case I come across is adding columns / fields to a table / collection, and not needing to ALTER TABLE and run a database migration as part of the deployment process to add said fields is extremely awesome.
This is not true.
I wrote Objectify, a popular third-party java API to App Engine's datastore. The data migration primitives worked out building Objectify are what ScottH built into Morphia, the Java "ORM" system for MongoDB. With a small number of primitives (mostly @AlsoLoad and lifecycle callbacks) it's possible to make significant structure changes on-the-fly with zero downtime.
This is, IMHO, the best thing about schemaless datastores. There's no longer any compelling reason (at least, in the datastore) to take down a system for "scheduled maintenance".
For more information, here is the relevant section of Objectify's documentation:
http://code.google.com/p/objectify-appengine/wiki/Introducti...
> "I find migrations painful and unnecessary."
A schema-less model neither makes a migration less painful nor eliminates it.
In MongoDB, what did you do when the data model changed?
Before I go into more details, MongoDB is great for most people who don't have a high transaction volume. It is easy to setup and easy to use. So if you are in this camp, MongoDB is probably a good fit for you.
We did about two months worth of extensive tests in our lab. Basically two things didn't bode well for us. One, the locking killed reading...we just had a hard time keeping the flow of writes and the flow of data to our statistics cluster alive. Yea, you could use replication but that too didn't work too well performance wise. Two, the sharding didn't seem that robust. As the cluster got bigger and bigger, we started noticing the overhead of keeping it up was getting to be too great. Rather than write in detail, I think this article covers some of the scaling issues we experienced:
http://blog.schmichael.com/2011/11/05/failing-with-mongodb/
We finally used a hybrid system. We went with Membase, now CouchBase, to handle immediate storage and we are now implementing Hadoop for our long term storage needs.
P.S. Our entire stack is a KV in nature.
So agreeing with a point earlier, if you don't like a write lock implementation, and have concerns about scaling, and have a huge transactional volume, just really not something that fits well with MongoDB.
I've been using Mongo now (currently using 1.8) for three (is it almost three now?) years, 2 million hits/day, with a replicated set, and while I've needed maintenance, reindexing, and (gasp) restarts on occasion, never had any of the problems identified by the author of this post.
Bottom line, sounds to me like someone was in over someone's head from an architectural standpoint, made a bad choice of MongoDB, and then blamed 10gen for his own lack of foresight. So while I empathize with the struggle, I fault him for not knowing his options in advance, TESTING first, then betting the farm on a fairly new opensource codebase.
LOTS of other database solutions that would scale better. Analyzing lots and lots of transactional stateless data with MongoDB map-reduce? Well, just kinda like killing yourself by trying to sprint up from the bottom of the Grand Canyon. "You really tried to do that?"
P.S. If your stack is KV then you should use a KV store.
MongoDB aside, why should you assume? You should test the heck out of any DB solution before using it to base your product on.
(I am not affiliated with either of them).
* http://blog.foursquare.com/2010/10/05/so-that-was-a-bummer/
* http://www.infoq.com/news/2010/10/4square_mongodb_outage
* http://groups.google.com/group/mongodb-user/browse_thread/th...
I like MongoDB, it is easy to setup, work with and to understand. I think it has an opportunity to become the mysql of nosql (in more ways than one)
Foursquare and 10gen (the makers of MongoDB) share USV as an investor.
https://groups.google.com/forum/#!topic/mongodb-user/UoqU8of...
I was sort of suggesting that this anonymous post may have come from somebody at Foursquare, since what is described kinda matches what happen there. The 'politics' element could also match because of the common investor - but I see that both 10gen and 4sq have responded here saying that they do not know who wrote this - which I believe.
First, I tried to find any client of ours with a track record like this and have been unsuccessful. I personally have looked at every single customer case that’s every come in (there are about 1600 of them) and cannot match this story to any of them. I am confused as to the origin here, so answers cannot be complete in some cases.
Some comments below, but the most important thing I wanted to say is if you have an issue with MongoDB please reach out so that we can help. https://groups.google.com/group/mongodb-user is the support forum, or try the IRC channel.
> 1. MongoDB issues writes in unsafe ways by default in order to win benchmarks
The reason for this has absolutely nothing to do with benchmarks, and everything to do with the original API design and what we were trying to do with it. To be fair, the uses of MongoDB have shifted a great deal since then, so perhaps the defaults could change.
The philosophy is to give the driver and the user fine grained control over acknowledgement of write completions. Not all writes are created equal, and it makes sense to be able to check on writes in different ways. For example with replica sets, you can do things like “don’t acknowledge this write until its on nodes in at least 2 data centers.”
> 2. MongoDB can lose data in many startling ways
> 1. They just disappeared sometimes. Cause unknown.
There has never been a case of a record disappearing that we either have not been able to trace to a bug that was fixed immediately, or other environmental issues. If you can link to a case number, we can at least try to understand or explain what happened. Clearly a case like this would be incredibly serious, and if this did happen to you I hope you told us and if you did, we were able to understand and fix immediately.
> 2. Recovery on corrupt database was not successful, pre transaction log.
This is expected, repairing was generally meant for single servers, which itself is not recommended without journaling. If a secondary crashes without journaling, you should resync it from the primary. As an FYI, journaling is the default and almost always used in v2.0.
> 3. Replication between master and slave had gaps in the oplogs, causing slaves to be missing records the master had. Yes, there is no checksum, and yes, the replication status had the slaves current
Do you have the case number? I do not see a case where this happened, but if true would obviously be a critical bug.
> 4. Replication just stops sometimes, without error. Monitor > your replication status!
If you mean that an error condition can occur without issuing errors to a client, then yes, this is possible. If you want verification that replication is working at write time, you can do it with w=2 getLastError parameter.
> 3. MongoDB requires a global write lock to issue any write
> Under a write-heavy load, this will kill you. If you run a blog, you maybe don't care b/c your R:W ratio is so high.
The read/write lock is definitely an issue, but a lot of progress made and more to come. 2.0 introduced better yielding, reducing the scenarios where locks are held through slow IO operations. 2.2 will continue the yielding improvements and introduce finer grained concurrency.
> 4. MongoDB's sharding doesn't work that well under load
> Adding a shard under heavy load is a nightmare. Mongo either moves chunks between shards so quickly it DOSes the production traffic, or refuses to more chunks altogether.
Once a system is at or exceeding its capacity, moving data off is of course going to be hard. I talk about this in every single presentation I’ve ever given about sharding[0]: do no wait too long to add capacity. If you try to add capacity to a system at 100% utilization, it is not going to work.
> 5. mongos is unreliable
> The mongod/config server/mongos architecture is actually pretty reasonable and clever. Unfortunately, mongos is complete garbage. Under load, it crashed anywhere from every few hours to every few days. Restart supervision didn't always help b/c sometimes it would throw some assertion that would bail out a critical thread, but the process would stay running. Double fail.
I know of no such critical thread, can you send more details?
> 6. MongoDB actually once deleted the entire dataset
> MongoDB, 1.6, in replica set configuration, would sometimes determine the wrong node (often an empty node) was the freshest copy of the data available. It would then DELETE ALL THE DATA ON THE REPLICA (which may have been the 700GB of good data)
> They fixed this in 1.8, thank god.
Cannot find any relevant client issue, case nor commit. Can you please send something that we can look at?
> 7. Things were shipped that should have never been shipped
> Things with known, embarrassing bugs that could cause data problems were in "stable" releases--and often we weren't told about these issues until after they bit us, and then only b/c we had a super duper crazy platinum support contract with 10gen.
There is no crazy platinum contract and every issue we every find is put into the public jira. Every fix we make is public. Fixes have cases which are public. Without specifics, this is incredibly hard to discuss. When we do fix bugs we will try to get to users as fast as possible.
> 8. Replication was lackluster on busy servers
This simply sounds like a case of an overloaded server. I mentioned before, but if you want guaranteed replication, use w=2 form of getLastError.
> But, the real problem:
> 1. Don't lose data, be very deterministic with data
> 2. Employ practices to stay available
> 3. Multi-node scalability
> 4. Minimize latency at 99% and 95%
> 5. Raw req/s per resource
> 10gen's order seems to be, #5, then everything else in some order. #1 ain't in the top 3.
This is simply not true. Look at commits, look at what fixes we have made when. We have never shipped a release with a secret bug or anything remotely close to that and then secretly told certain clients. To be honest, if we were focused on raw req/s we would fix some of the code paths that waste a ton of cpu cycles. If we really cared about benchmark performance over anything else we would have dealt with the locking issues earlier so multi-threaded benchmarks would be better. (Even the most naive user benchmarks are usually multi-threaded.)
MongoDB is still a new product, there are definitely rough edges, and a seemingly infinite list of things to do.[1]
If you want to come talk to the MongoDB team, both our offices hold open office hours[2] where you can come and talk to the actual development teams. We try to be incredibly open, so please come and get to know us.
-Eliot
[0] http://www.10gen.com/presentations#speaker__eliot_horowitz [1] http://jira.mongodb.org/ [2] http://www.10gen.com/office-hours
Although we don't yet have a fixed office hours schedule, we typically hold them every 2 weeks. The exact dates are announced via the local MongoDB Meetup Group°; we always hold the hours at "Look Mum No Hands" on Old Street.
At least one (and often several) of our Engineers make themselves available during this time to answer any questions and assist with MongoDB problems.
I envy how all your (potential) customers are from California.
MongoDB simply gets better in any version and it is indeed a reliable platform, at least as human beings (employees) are.
It might be helpful for 10gen to put together a short doc on what to watch out for evaluators.
I don't think a short doc is of any help for evaluators. You shouldn't be basing your decision on 400 words and some bullet points. If you're serious about your datastore then you should treat it seriously.
http://www.10gen.com/presentations/mongoboston-2011/schema-d... http://www.10gen.com/presentations/mongosf-2011/practical-sc...
Wedge Martin CTO Badgeville
We have meticulously kept a QA server pair around and the only time when I have ran into a data loss problem was when I have hosed one of those -- but only one and even the QA department could continue (and hosing that server was me not knowing that Redhat 5 had separate e4fsprogs and e2fsprogs, only partially MongoDB fault but now it works without O_DIRECT so even this would not be a problem any more) . Never understood for example how could foursquare get where they got to -- didnt they have a QA copy similarly?
You do realize that 1.8 vs 2.0 is not eons ago, but just a few months, right? And you do realize that the cavalier-throw-all-caution-to-the-wind development attitude that cause all this problems can and does continue to exist? You don't eliminate that just because you added a transaction log (as late as in 1.6, IIRC).
There have been plenty.
(Though there weren't a lot of blog posts about it, because the word blog had not been invented yet; blogs developed along with... MySQL.)
It will be interesting to watch Mongo as it matures over the next ten years. Unlike MySQL, it is competing against ubiquitously-deployed, well-known, well-worn open-source RDBMS packages, so its history is unlikely to unfold in the same way that MySQL's did.
Indeed it's the only database system I have ever used where a system with a single transaction running only multi-row inserts into a table can (and frequently does) deadlock against itself. Don't get me wrong, time was when it was easier to use than PostgreSQL but that time is long since passed.
One area I have continued to recommend MySQL has been in areas of content management but to be honest in many of these areas, NoSQL is actually a better fit.
MySQL has a niche too. It's somewhere between that of a NoSQL database and that of a real RDBMS. MySQL does well for single app databases (as NoSQL does), but where the relational data then needs to be fed through other database systems for multi-app access.
I know Facebook seems banal because we interact with it in some way several times a week, but is your head wrapped around how huge that thing is?
One of my customers logs certain web data into a MySQL database and loads/processes it in a PostgreSQL database every day. The data is then accessed in Pg by at least three different applications.
That's reasonable, btw.
Derek Harris puts the larger point about Facebook's trouble with MySQL: "By and large, [MySQL] does [for Facebook] what it’s designed to do, which is to keep up with the myriad status updates and other data that populate users’ profiles. Rather, [the problem is] that Facebook had to expend so much money and so many man-hours to get there."
http://gigaom.com/cloud/is-stonebraker-right-why-sql-isnt-th...
yes
> Stop using Java?
yes
Tongue-in-cheek aside, the author's point is that regardless of its current status, MongoDB has been pushed on a lot of people hungry for performance/simplicity; in that singular pursuit they may be setting themselves up for disaster later on. Most developers have a (perhaps unspoken) assumption that a successful write to a database means that data Will Not Disappear. If Mongo violates this assumption, then either developers' attitudes have to change or they should look at other software to avoid being bitten.
Take something like sockets: by using TCP, I am telling my development environment that I would like an unbroken, sequential stream of traffic to another endpoint. Just as importantly, I would like to be notified if this ever is not the case. If I discovered errors in my TCP stack, I want those fixed pronto because any kind of workaround would be reimplementing the very task TCP is meant to cover -- I might as well write my own sequencing and retransmission logic on top of UDP!
Most of the people who are excited about mongo, have never used it in a high volume environment, or with a large dataset. We used it for a medium sized app at my last employer, with paid support from 10gen, and everyone on the project walked away wishing we had stayed with a more mature data store.
Of course things work well when traffic is low, everything fits in memory, and there are no shards.
My focus in starting Citruseaf wasn't features, it was operational dependability. I had worked at companies who had to take their system offline when they had the greatest exposure - like getting massive load from the Yahoo front page (back in the day). Citrusleaf focuses on monitoring, integration with monitoring software, operations. We call ourselves a real-time database because we've focused on predictable performance (and very high performance).
We don't have as many features as mongo. You can't do a javascript/json long running batch job. We'll get around to features - right now we're focused on uptime and operational efficiency. Our customers are in digital advertising, where they have 50,000 transactions per second on terabyte datasets (see us at ad:tech in NYC this coming week).
Here's a performance analysis we did: http://bit.ly/rRlq9V
This theory that "mongo is designed to run on in-memory data sets" is, frankly, terrible --- simply because mongo doesn't give you the control to keep you in memory. You don't know when you're going to spill out of memory. There's no way to "timeout" a page cache IO. There's no asynchronous interface for page IO. For all of these reasons - and our internal testing showing page IO is 5x slower than aio; the reason all professional databases use aio and raw devices - we coded Citrusleaf using normal multithreaded io strategies.
With Citrusleaf, we do it differently, and that difference is huge. We keep our indexes in memory. Our indexes are the most efficient anywhere - more objects, fea. You configure Citrusleaf with the amount of memory you want to use, and apply policies when you start flowing out of memory. Like not taking writes. Like expiring the least-recently-used data.
That's an example of our focus on operations. If your application use pattern changes, you can't have your database go down, or go so slowly as to be nearly unusable.
Again, take my comments with a grain of salt, but with Citrusleaf you'll have great uptime, fewer servers, a far less complex installation. Sure, it's not free, but talk to us and we'll find a way to make it work for your project.
(PS I know you're enterprise software, but still).
With regard to nomongo's post, 10gen can check their record and say whether they did or didn't have a customer with premium support account with similar use case and issues. 10gen can also counter such complaints with testimonials from customers with similar use cases.
But note that nomongo's post is not about individual issues but about his concern that 10gen's priorities are misplaced which he should have wrote first instead of last. Rest was just about how his concern came about. Current status of technical issues he experienced are irrelevant to his concern.
Performance benchmarks stop being meaningful when you realize that you can't fix the problem you're having without committing to a system-wide shutdown of unknown duration.
The main point that the author makes is that the creators of MongoDB do not follow rigourous practices. If this doesn't bother you, please go right ahead and use anything you wish.
I hear that /dev/null is really zippy these days.
As a user of MongoDB and Cassandra I am very interested in the sort of discussion that comes out of such postings.
I had to use MongoDB recently, and I wasn't very pleased with it. It wasn't really appropriate for the project, which had data that would have fit better in a relational DB.
nomoremongo 4 hours ago | link I'd appreciate if someone would submit this story for me. http://pastebin.com/raw.php?i=FD3xe6Jt
What's up with the trolling here. Who are you and what company do you work for that has had all those problems you mentioned ?
Besides, calling a position you don't agree with "trolling" with no further argumentation is 4chan level of discourse, and I know what I'm talking about when I say this. I will not take a side in this discussion because I'm not qualified to voice an opinion over things I do not understand well enough (databases), but I had to point this out.
as it stands now it's not fact based and could as much be opinion as there is no way to weight the merit of the claims against anything substantial :(
I just dislike calling anyone who prefers to stay in relative anonymity (for whatever reason) or is simply new to a community "not credible", at least if it's only because of those attributes. It's a thinly veiled ad hominem.
(Sorry, possibly excessive snark. That said, I think that blog post is a good example of one of this pastebin author's points: at least historically, benchmark numbers have been a big focus for Mongo developers.)
I don't think it's a stretch to say that any database that has 25 servers should be able to handle at least 8 million operations a second.
I haven't used it in production (yet), but I would have no fear of using it today. I would run regular consistency monitoring and validation around critical data just like I do with our SQL databases.
I'm willing to take my part of the pain and inconvenience in making technology like this stable.
You could have written this about any adolescent SQL server BITD. All the tools you use today had to go through this process.
For me Mongo is awesome and getting more awesome. Mongo and technology like it is the reason I still get excited about writing new apps.
http://news.ycombinator.com/item?id=2538037
I'm not a Riak user, but I agree with Basho's analysis on this case.
On a side note, we also looked at MongoDB and, after running a few tests, we concluded that it is a glorified key-value pair storage. That said, we did use it in a few small-scale projects and it works great.
The bottom line: choose the right tool for the job and don't bitch about the tools when you fail.
The failure exists because many developers don't ask a few key questions up front:
1) What exactly can the database do for us? 2) Which of these do we need? For example, is the database going to be a point of integration? 3) What failsafe or security measures do we want to count on in the database?>
These don't always have objectively right/wrong answers but failure to ask the questions leads to poor use of databases regardless of what technologies are chosen.
* Yes, playing with Mongo is playing with fire. Know what you are doing. We don't claim that you should use us as your only database.
* We're going to fix these issues soon. The beginning days of MySQL etc were also frightening, with Oracle and MS SQL Server admins warning of all the dangerous things that can happen.
If they confront their issues, I think it's just a matter of time before Mongo wins the NoSQL race. They have what matters most - good people, a brand, and great expectations from customers.
The fact that the 32-bit version also truncated data with no warning doesn't make me hopeful, either.
Some of you guys who were all aboard the NOSQL UBER ALLES hype train a year or two ago now seem to be swinging back - with scrapes and bruises from some truly harebrained misdeployments, no doubt - to a reactionary 'All NoSQL are doomed to reimplement everything relational' nihilism. Back to shitty OR tools and ugly-ass joins for everyone, damnit! Harumph. I could write a novel just quoting and responding to some of the stupid pronouncements and prescriptions for correctness on these Mongo threads' comments.
Anyways. With regards to this specific post:
Let's rewind a couple of years. I work for a significantly smaller company than our anon raconteur, from the sound of it. At roughly the same time as he adopted Mongo, I was also looking hard at it, to solve some problems where the relational options available to us weren't going to cut the mustard. Damn, did Mongo look cool, fun even. The flexibility of having arbitrary object graphs in it and querying down into subdocument properties with real indexing on them, well, it sets nearly any developer's heart a-flutter, particularly those of us who work on dynamic web stuff a fair bit.
Sadly, I have to be an engineer and pragmatist first, I have to think about much more than what is sexy and comfortable for devs. I've been through my share of 3AM wake-up world-enders, I've learned the hard lessons. I considered variables like basic maintainability by ops people, credibility of the vendor, track record, robust redundancy and availability solutions, how far up shit creek we'd be in a disaster recovery scenario, etc. And after thorough research I decided that, for my much smaller company which can afford to be judiciously bleeding-edge where it makes sense to, Mongo was just not clearing the bar. I sucked it up and used unsexy properly normalized relational database tables, then utilized memory caching and async updates to try and paper over the performance issues inherent in that scheme.
What was anon doing? Charging full steam ahead into the wild unknown with Mongo, on an effort that was apparently important to a userbase of millions at a "high profile" company. That's some mighty responsible stewardship of the company, or even just the IT department's, broader concerns right there. Now, I understand that it totally makes sense to have used Mongo 1.x as a scrappy startup on a greenfield project, no problem. But this guy was in a different situation. At that scale in a BFC, conservatism rules, and it rules for a reason.
I think I am starting to understand why anon is anon.
In any case, we're likely going to roll with Mongo soon. It is indeed maturing, and I'm a lot more comfortable with it on all of my criteria these days. I have possibly read more of the JIRA issues than some of the devs, and they are prioritizing the Right Things - at least for my tastes. By my estimation it is on the right track.
Even having not used it in production yet, I can identify some things people are complaining about here as complete and utter RTFM-fail, misunderstanding of what it is they're deploying and whether what they expect out of it is realistic before they begin. I understand the tradeoffs of Mongo, and in my particular situation they make good sense.
If you are going to use the database just to store data structures form your program, you might as well use NoSQL db's. However, in most cases, you get integration and migration wins by:
1) Placing your engineering effort on the database. Looking at the sort of real world data you are collecting, modelling it well in the database and then presenting an API to the application. The API will either be a relational one (i.e. views) or a procedural one (stored procedures). After a couple of iterations, the schema shouldn't be being fundamentally changed too much though there could be some minor tweaking.
2) Now, with a good API you can build an application on the database using a methodology of your choice. This could be done in an agile way.
Now if integration is not a goal, then sure you can do all the data validation in your application and you can use NoSQL databases. But relational databases are also powerful integration tools in their own right. I can't imagine LedgerSMB, for example, doing well on anything else for this reason alone.
There is/was a LOT of hype in NoSQL. Hype and very little understanding what NoSQL is about and specifically why/when choosing a NoSQL database makes sense and when it does not.
It is not about SQL vs. not. It is about consistency, availability, and partition tolerance, and which of these you are willing to give up. Surprisingly few people know about the CAP theorem and what it implies.
Generally there two main reasons why you switch to NoSQL (Not Only SQL) databases. 1. You need to scale out (add more storage and query capacity by adding more machines). 2. You do not want to be locked into a relational schema.
There is no magic in NoSQL! To scale out these stores give up exactly those features that would impede scaling out (for example global transactions).
What one has to realize that you give up a lot by letting go of relational databases: Fast ad hoc queries, transactions, consistency, and the entire theory and research behind it. I don't see why relational databases are "unsexy". A good query planner is almost a work of art and it is amazing what they can do. In fact we use them alongside HBase.
Instead of ad hoc queries you either get slow map/reduce type "queries" or you need to plan your queries ahead of time and denormalize the data accordingly at insert time.
You better have very good reasons for the switch.
When we evaluated NoSQL stores a while back (for #1 type problems) I was quite the skeptic. We looked at Riak, Redis, MongoDB, CouchDB, Cassandra, and HBase). Eventually we settled on HBase because needed consistency over availability and we needed more than just a key value store, and we already some Hadoop projects... and I started to drink the cool-aid :)
Personally, I am not a big fan of eventually consistent (but highly available) stores, because it is extremely difficult to reason about the state of the store; and the application layers bears a lot of extra complexity. But your mileage may vary.
HBase of course is new as well, and I needed to start fixing bugs and adding new features that we needed.
As with "Java is better than C++" type discussions, here too, what store to use depends on the use case. As parent points out any hype about anything is a bad thing, because it typically replaces reasons as an instrument of decision making.
(not sure what I was getting at, so I'll just stop here).
There are plenty of things about MongoDB I don't like but this OP is a total coward. If you've got something to say, put your name on it and come out in the open.
This type of post is the worst of its "hiding behind Internet anonymity" kind.
And for the record, I don't think Oracle is behind this. They're confident in their Exadata offering and have little to gain by posting this kind of crap around MongoDB. Besides, Larry Ellison has never been afraid to openly taunt his competitors.
The thing that worries me most is that this article got so many upvotes.
My question is, given Mongo and the other NoSQL solutions, has anyone come up with a comparison of strong and weak points across different application types? Feature lists really aren't always useful - as noted about things like code maturity, etc.
It seems to me that NoSQL does not really bring speed. Just scalability and a different model. Hopefully most of them don't lose data at random. PG certainly doesn't, even with sync() off.
I have not tested the scalability of PG.
Aren't joins one of the things that NoSQL loudly and proudly announces that it isn't suitable for?
If the cause is unknown, how can you blame it on a given piece of software?
"Oh THAT", say Mongo boosters. "You should have read the IRC logs of June 22nd", they continue, "there was a 3 line patch posted in the channel. It totes fixes that problem".
MongoDB (along with PostgreSQL, RDF data sotres, and sometimes Neo4J) is solidly in my preferred tool set.
I agree with the author that MongoDB is green, maybe not quite ready for prime time yet. All things considered, I realize we took a risk by switching and while I am quite happy with MongoDB, I do worry that at some point we will experience a failure condition we might not be able to recover from.
MongoDB is awesome at certain things. But it is still not at a tried and true level as say PostgreSQL or MySQL.
I am skeptical of the article but only because it is all too easy to fault new projects. However I would be curious to know 10gen's development practices as compared to say Postgres or SQLite (I have heard awesome things about SQLite's development testing).
What is your comment about code written? Is it maintainable? Is it modular? Doe s it seem well written?
Responding to anonymous flames in the internet is a waste of time.
Edit: to the downvoters, this is a serious question.
No, of course not. But the point is that it would be easy to generate a post like this just by going back over the critical bug list for previous versions, and throwing in an unsubstantiated claim of 'mysterious data loss.' And Oracle does have the incentive and the means to engage in an old fashioned Microsoft-style FUD campaign. They've already launched their 'embrace-and-extend' strategy: http://www.oracle.com/us/corporate/press/519708 .
And, given that none of the serious allegations the OP made are verifiable, it matters that much more.
how gullible most of you are
You seem too convinced of your own greatness to seriously consider the possibility that maybe most people here are actually sensible and don't rush to judgments. To me, this post portrays you as an 18-year old that was the smartest in his highschool, but has yet to realize and accept just how awfully many people out there are smarter and wiser. God help the people around you if you're older than 28.
So, #5, #1, then the other 3 in some order :)