MongoDB 6 Released
mongodb.com
mongodb.com
> The performance of $lookup has also been upgraded. For instance, if there is an index on the foreign key and a small number of documents have been matched, $lookup can get results between 5 and 10 times faster than before. If a larger number of documents are matched, $lookup will be twice as fast as previous iterations. If there are no indexes available (and the join is for exploratory or ad hoc queries), then $lookup will yield a hundredfold performance improvement.
It should have been done long time ago. Better late than never.
MongoDB is anything but dead.
Also MongoDB isn't even 15 years old, so how could it have died 15 years ago?
Disclaimer: ex-MongoDB employee.
MongoDB blends the commercial aggressiveness of Oracle with the audit mindset of IBM. The sleaziest in the game.
It’s also strange because they keep demanding license fees and asking to audit and I just deny and tell them to buzz off.
They remind me of Oracle. It also makes me wonder if there’s some legal compulsion that could force them to do discovery. Based on their behavior I would not use mongodb.
Oracle eventually faded in relevance similar to IBM. So will Mongo. It will be around as a relic living by auditing the installed base.
But IBM? You are having a laugh. IBM was there at the start of the computer industry and they have survived every single generation of change since, getting stronger each time.
Saying IBM has faded in relevance is absolutely farcical.
The S and P is up 50%. https://finance.yahoo.com/quote/%5EGSPC/
Go back 10 years and IBM is down roughly a third while the S and P has almost tripled. This is while IBM has been doing massive buybacks to raise the price.
Is that farcical?
What’s interesting is a Mongo employee looking at IBM as a role model. This confirms the “get in and then and then squeeze your customers” strategy.
Just be careful. As an employee, the endgame isn’t pretty when the company realizes that young auditors are cheaper than old salespeople and engineers.
Companies that adopted this technical debt during its prime (2010-2015) and are now paying for enterprise licenses and support to service that debt.
Personally I disliked it, primarily due to personal bias towards RDBMS (most data is inherently relational and I saw a lot of unnecessary hoops getting jumped through to join data) and also because the driver situation was absolutely terrible when I had to work with it. Custom drivers to serialize almost any JSON data was incredibly annoying.
From a developer standpoint it's alright, we're getting to the scale now where we're thinking about migrating to a more global architecture and I'm glad we're using something like Mongo over trying to hack this out with Postgres.
The standard issues with trying to use MongoDB like a regular ol' SQL DB still apply though, and our developers (me included) still fall into using anti-patterns and have to speak with solutions engineers once in a while.
Can you share the use cases? Why Mongo works better than Postgres?
Circa 2013 or so I was working for a regional newspaper group. They decided they wanted a weather section. So we subscribed to, iirc, Accuweather.
I wrote a script that would pull it down at the update interval (Every 15 minutes I think it was)
This was, for the time, for a shoestring outfit with only a few servers, a lot of data.
Something like 50k locations, with around 30 “rows” for each location - current conditions plus hour by hour going out a bit more than a day.
Loading this into our poor little MySQL server was… slow.
So I just setup a small mongo instance, and loaded/read from that. Worked great… we didn’t care about durability so we dodged that whole minefield. Mongo had a way to atomically swap two tables… so the import script would load into a scratch table, then swap that into the one the web server actually read from.
Loaded super fast since we didn’t care about durability, and read performance was more than adequate for the very simple queries we ram against it.
(To give you a feel for the era, this is when MyIASM was the default table store, and didn’t support fks or transactions)
With Mongo, its distributed by default. And if your data keeps growing, you simply add more nodes without any additional changes in the application code.
Live resharding indeed helps for a sharded cluster that already exists.
Of course it haa a perf impact - nothing is free.
JSON indexing is quite advanced in mongo. Postgres is catching up (gin indexes on jsonb arrays). So are aggregations on json
MongoDB Atlas - fully managed and by MongoDB core committers
We don't have a lot of multi document ACID requirements.
We are on GCP and cloud sql is a very basic postgres deployment and we don't want to mange infra
The most obvious one being where you are requesting data and related data based upon a unique business identifier.
NoSql DBs mostly make this both trivial and fast.
Postgres and other SQL options become relevant where aggregation and reporting become primary considerations.
NoSQL Databases arose from a realization that sometimes you don't need all the features of a relational database, for example:
- Redis which at the most basic level is a key value cache
- MongoDB which stores (denormalized) documents
NoSQL Databases like MongoDB are best when:
- All data related to a certain entity can be reasonably self contained (i.e. does not require relating to other possibly dynamic pieces of data)
- referential integrity (knowing that User.storeId can be treated as just a string) does not need to be maintained
- Constraint checking does not need to be performed or can be performed at the application level
- Schemas are either wildly variable or do not change at all, or checking them just isn't important.
The best example I hear often is a news site or blog -- if your main model is something like an Article that contains the author, content, tags and all data necessary to display one entry (and 99% of the time you get one Article and are not required to request related data that exist in separate collections), then NoSQL makes sense.
It's a tired conversation I think people have had repeatedly for a long time, so I won't go into it again (I'm also VERY biased towards RDBMS and in particular Postgres) -- would love to hear from experienced MongoDB proponents though!
One case I know Mongo was trusted for very early on was large scale out use cases, and after WiredTiger their execution engine improved immensely as well. I assume it's still great for that, where scale out is often quite lacking in RDBMS or not in the core experience.
[0]: https://en.wikipedia.org/wiki/Relational_database#Relational...
RDBMS puts a lot of effort to support a wide range of ACID properties. However which also make it very difficult to be used as cluster.
So if your bussiness data is too large to be hold by a single instance of database, you will need a database cluster. And maybe someday, you want to get better performance, then you change your schema to remove some data constraints. Like removing FK, use application logic instead of storage procedure, etc.
That's the reason why we need NoSql database.
If OLTP is not the key part of your business, and it is expected to store a large amount of data in future. Then it would be better to carefully design your data schema so you can use NoSql database instead of a traditional RDBMS.
E.g. use nested document instead of FK to store 1 to 1 relationship. So you can take advantages of single document atomicity. Use array to store 1 to many relationship instead of an additional mapping table.
> RDBMS puts a lot of effort to support a wide range of ACID properties. However which also make it very difficult to be used as cluster.
Note that while common, ACID is actually not a requirement for RDBMSes -- there are NoSQL datastores that provide acid guarantees, like FoundationDB[0].
> So if your bussiness data is too large to be hold by a single instance of database, you will need a database cluster. And maybe someday, you want to get better performance, then you change your schema to remove some data constraints. Like removing FK, use application logic instead of storage procedure, etc.
I agree with the point, but I want to note that the vast majority of apps do not have data too large to be held by a single instance, especially with the eye-watering density of hardware these days.
Some proof for my essentially wild conjecture:
- Reddit started with just postgres[1]
- LetsEncrypt (the reason most of the internet will have TLS in the future if not already) supports over 235MM sites with just one MySQL box[2]
Now it's not that you can't mis-use RDBMS (Postgres), or that it's always the right tool for the job, but I just want to note that it's very possible to get very far with application size without scaling out horizontally. Scaling out horizontally & compromising your data model should be the last options you pursue, IMO.
Also, that said, Citus for postgres is now fully open source[3], TimescaleDB has been open source and only got open-er[4] (they have a clustering mechanism) so this diminishes the use case for NoSQL going forward. This means that the specific use case for NoSQL is eroding somewhat.
> If OLTP is not the key part of your business, and it is expected to store a large amount of data in future. Then it would be better to carefully design your data schema so you can use NoSql database instead of a traditional RDBMS.
I'd argue that you should default to OLTP and only deviate when you need the extra power, but we'd probably agree to disagree there :)
[EDIT] Highscalability.com has a great writeup on this from 2010 (!) that as I skim through still looks mostly relevant:
http://highscalability.com/blog/2010/12/6/what-the-heck-are-...
[0]: https://www.foundationdb.org/
[1]: http://highscalability.com/blog/2013/8/26/reddit-lessons-lea...
[2]: https://letsencrypt.org/2021/01/21/next-gen-database-servers...
[3]: https://www.citusdata.com/blog/2022/06/17/citus-11-goes-full...
Yes, most of NoSql provides some kind of ACID guarantees, however not as good as RDBMS. MongoDB also provides single document atomicity. But in RDBMS you can configure the ACID properties.
> but I want to note that the vast majority of apps do not have data too large to be held by a single instance
I agree with that. For me, the order would be: 1. Do not use database 2. Use SQLite 3. Use single instance RDBMS 4. Use single instance NoSql 5. Use single instance RDBMS + NoSql cluster 6. Use RDBMS cluster
> I'd argue that you should default to OLTP and only deviate when you need the extra power, but we'd probably agree to disagree there :)
Personally I would prefer NoSql when the business model fits some specific patterns. But I agree with you that.
The article of Highscalability.com is very useful, and also some other articles. I did not know the site before, thanks for sharing.
And multi-document, in sharded clusters. 2018: https://www.mongodb.com/blog/post/mongodb-multi-document-aci...
>>>But in RDBMS you can configure the ACID properties. https://www.mongodb.com/docs/manual/reference/write-concern/
Yeah it’s so funny, HN seems to rediscover way of thinking every so often! I think it’s why SQLite projects are so popular (and of course how well built and popular SQLite is)
Am I missing something here?
I don’t think that’s right though? Requesting data and related data is the purview of RDBMS, unless your example was a completely denormalized single object (I know Mongo supports links between objects as well but that doesn’t seem to be what you’re saying?)
Also the line point about SQL based databases being relevant when reporting and aggregation misses the importance of relations and operations in relations that is the point.
Maybe the comment was focused in on “SQL” rather than using it as a shorthand for “relational database” like most people do. Yes SQL makes aggregation and reporting easier but it’s primary job is data retrieval, and in most cases via an identifying primary key.
Hosting and infrastructure?
Sure for your weekend project there are plenty of alternatives. At enterprise level you aren't paying for just the base product you're paying to have someone else worry about all the other stuff that keeps it up and running.
Yes you can find Couchdb hosting services but it's very nice to have the company that builds the product also control the hosting.
I've worked at a company that was fairly large MongoDB customers. Even though MongoDB was a major part of our overall product there was never a second of considering hosting our own solution, and there was likewise never a time I remember Mongo being responsible for a major outage or other infrastructure issue. That's worth quite a lot of money to not have to worry about an essential part of your own internal product infra.
(Honest answer: a company can continue way longer than you think just supporting legacy customers - need Lotus Notes? https://www.hcltechsw.com/notes )
Also, I look at projects which have survived over a decade rather fondly. ;)
Here is a few I know are public references:
MetLife, Epic Games, Bosch, Inland Revenue (UK), Department of Work and pensions (UK) Barclays, HSBC, Boots, Forbes, Toyota, Sanoma, Intuit, Verizon.
MongoDB Community Edition is a powerful software.
but in all seriousness. hstore is good enough for 99% of mongodb users
Would it be feasible to use both, from within the same application, depending on the type of data in question?
The SQL vs. No-SQL debate has been going on for along time. Why not use both? Has anybody tried that?
Reducing the cognitive load is important in large code bases.
Heck, even a single one on a good machine is sufficient.
It has a colorful mix of SQL and NoSQL constructs, interacted on SQL queries.