I’ll Give MongoDB Another Try In Ten Years

If you tell a database to store something, and it doesn’t complain, you should safely assume that it was stored.

This has nothing to do with the 2Gb limitation. Nowhere in the documentation does it mention that it will silently discard your data. What will happen with the 64-bit version if you run out of disk space, more silently discarded data?

I know a lot of you may have cut your teeth on MySQL which, in its default configuration, will happily truncate your strings if they are bigger than a column. Guess what? Anyone serious about databases does not consider MySQL to be a proper database with those defaults. And with this, neither is MongoDB, though it may have its uses if you don't need to be absolutely certain that your data is stored.

EDIT: Thanks for pointing out getLastError. My point still stands, since guaranteed persistence is optional rather than the default. In fact, reading more of the docs points out that some drivers can call getLastError by default to ensure persistence. That means that MongoDB + Driver X can be considered a database, but not MongoDB on its own.

I'm just struggling to imagine being willing to lose some amount of data purely for the sake of performance, so philosophically it's not a database unless you force it to be. Much like MySQL.

EDIT2: Not trying to be snarky here, but I would love to hear about datasets people have where missing random data would not be an issue. I'm serious, just want to know what the use case is that MongoDB's default behaviour was designed for.

EDIT3: (Seriously) I'm sure MongoDB works splendidly when you setup your driver to ensure that a certain numbers of servers will confirm receipt of the data (if your driver supports such an option), nowhere am I disputing that. But that number really should have a lower bound of 1, enforced by MongoDB itself. And to the guy who called me stupid: you are what's wrong with HN.

It's legit to criticize a language or a database. However, it seems to me that when MongoDB gets involved, the tone is far more aggressive and defensive. What's up with that? It's just software, bits and config files. It's not like someone called your mom a harlot.

Here's what I think. New developers, for a long time, have come into the industry and become overwhelmed with everything they need to learn. Let's take typical database servers. Writing a SELECT is easy enough, but to truly be an expert you have to learn about data writing operations, indexing, execution plans, triggers, replication, sharding, GRANTs, etc. As it's a mature technology, you start out barely an apprentice, with all these experienced professionals around you.

In recent years, software development has really been turned on its head. We're not building apps using the same stack we've used for a long time: OO + RDBMS + view layer + physical hardware. The younger the technology, the better, it seems. In theory, a 3 year developer and a 20 year developer are now pretty equal when we're talking about a technology that's been around 2-3 years. That wouldn't be true if we were dealing with say, OO design patterns. (Even when new languages come along, you still get to keep your experience in the core competencies.)

Attacks on these new technologies are perceived as an assault on this new world order, and those who have walked into being one of the "newb elite" respond emotionally to what they see as a battle for the return to the old guard. Am I totally off base here?

Aside from that, though, the 32 bit limitation is clear in the documentation and present on the download page. It's fine not to read the documentation before you use something but you can't then complain that it did something you did not expect. Mongodb is a little different from other databases. So is Redis. You can't blow everything off that is conceptually different.

I've noticed a trend across about 20+ candidates, all of whom are smart people: people are using Mongo without actually understanding what the hell it's trying to solve by getting away from the RDBMS paradigm.

I'm not sure if this is because 10gen markets it as a general purpose tool, but I have yet to talk with a candidate who can actually describe why they were using the DB vs. a SQL database. I'm all for learning new things, but I can't help but wonder if the string of negative MongoDB posts is coming from people who pick it b/c it's new, then realise pretty far in that this is nothing like a normal DB, and "having no schema" isn't really a reason to go with a tool as foundational as a data store.

I think Mongo is great for really specific problems that its designed to solve. It's probably pretty bad for a general purpose tool, but I'd be surprised if anyone serious actually considers it one.

There is a discontinuity between the ease-of-use story and the blame-the-user story, regardless of how well documented the async insert behavior is.

And it doesn't have to be this way. There are ways of designing interfaces, APIs, and even naming that go a long way to prevent your users from shooting themselves in the foot.

Take postgres. It also supports at least a couple kinds of async insert, one of which is a part of libpq (postgres C client library). It's called "sendQuery" and it's documented under the "Asynchronous Command Processing" section. It's hard to imagine a user trying to use that and expecting it to return an error code or exception. Even if the user doesn't read the docs, or reads some fragment from a blog post, they will still see that the name suggests async and that it returns an int rather than a PGResult (which means it obviously doesn't fit into the normal sync pattern).

There is no reason mongo couldn't be clear about this distinction -- say, rename "insert" to "async_insert" and have "insert" be a wrapper around async_insert and getLastError. But instead, it's the user's fault because they didn't read the docs.

Careful API design is important to reduce the frequency of these kinds of errors. In postgres, it's relatively hard to shoot yourself in the foot this badly in such a simple case. I'm sure there are gotchas, but there is a conscious effort to prevent surprises of this sort.

1) it does not behave exactly like SQL

2) the user didn't read any more than a Quickstart Guide

3) the user fundamentally misunderstands the aim of the new technology or the application it is intended for

Ember.js suffers from the same ignorance.

What makes it worse is all the morons who upvote without even reading the detail purely because the title reinforces some misconceived bias they already have.

'NoSQL' is part of the problem. This technology has absolutely no comparison with SQL other than it persists data.

This brings me back to the recent discussion about reading other people's code: it is almost certainly smarter to extend an existing database until it's capable of meeting your needs, rather than write one from scratch.

The fact that many programmers don't see it that way is a testament to their irrational fear of diving into other people's code.

However, it starts to feel like Anti MongoDB is just considered cool today, when I see someone that worked with MongoDB for a year, upgraded to 2.2, knows it inside out and still hates it, I would listen, and start to worry. but until then, I'm going to keep using it, and saving time.

In all seriousness, I built a 10 machine Mongo cluster, talked with a 10gen consultant a full day, went to Mongo meetup, and ran all sorts of benchmarks before ever using it in production. I still don't feel like I have the expertise to write a snarky blog post about it.

http://www.mongodb.org/display/DOCS/getLastError+Command

The MongoDB "way" is that clients know the importance of their data and can choose write strategies which make the proper trade-off between insertion throughput/latency and durability/consistency.

So, assuming you are writing an ecommerce application, here's where I think these flags come in.

- Session data: fsync = true. Wait for a response, and ensure it's written to disk

- Internal web analytics: safe = false. Who cares if it's written, I've got an application to serve!

- Orders: fsync = true. I know, RDBMS, transactions, blah blah blah.

People tend to look at NoSQL and wonder why it doesn't function like MySQL, then they loudly complain how bad the software is. Nobody is writing articles about how Memcached doesn't function like MySQL.

Yes, I realize that there's a "safe=True" option to my python driver. But I'm writing to a database. As others have said here and elsewhere, the default behavior of a database and its drivers should be to complain loudly when a write fails. It is ridiculous that safe!=True by default. If I want to turn off this feature to improve performance, I will.

Yes. Without question.

Is this his own fault for not reading the documentation and understanding that he should have opted for the 64bit version outright?

Yes. Without question.

Exception throwing database drivers are a relatively new thing not an old thing. The only thing MongoDB does differently is that the writes are fire and forget in that the database hasn't returned a response of any kind when the function returns.

In native code you can forget about using exceptions in a database driver because exception handling can be exceptionally broken on some platforms. SmartOS I am looking in your direction.

There seems to be a number of people commenting, telling you to read the documentation, but I'm with you, that is completely counter-intuitive behaviour and should be viewed as a bug.

Another problem with Mongo I never heard anyone else raise is that there are no namespaces. If I install Mongo, all the tables/collections live in the same namespace. What if I want to use it for multiple projects? How do other people solve this problem?

These are really not points to be discovered in chapter whatever of the docs.

- Download, Brief 3rd party tutorial, Production, Break, Complain, RTFM / Complain

- RTFM, Smile, Download | Move On, Staging, Production

Seems most of the issues from this article came from a lack of reading and investigating.

In general it feels like Couch actually takes storing data seriously. Append-only and whatnot. It's slower and a little bulkier than Mongo, but it does the important things right (1.0 bugs notwithstanding.)

I'd love a follow-up blog post on your experience with Couch.

another thing I didn't realize was that because of the memory mapped systems which i guess is fine performancewise it's hard to estimate memory usage on a machine. from what I understand there is no possibility to limit the memory usage. Which means that the only way you can limit the amount of memory used is by keeping the size of the database below your memory. quite important things to know imho.

here's an interesting post mentioned in the comments: http://www.zopyx.com/blog/goodbye-mongodb

I understand having another node or two for fail over but I reckon with the spec of the largest offerings from AWS or Linode most people will never need to worry about this and can manage everything on one Postgres or MySQL db. Why complicate things before you have to.