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1) It is wrong to evaluate a system for bugs now fixed

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).




> Bullshit. You, personally, are demonstrating the opposite with redis which is about the same age as MongoDB (~2 years).

Apparently you have no idea how many critical bugs have been fixed in Redis...

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I agree with your responses to 1 and 2. I take issue with the example for 3 though because Redis is nowhere near the complexity or feature set of MongoDB.

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I don't think that counts as an argument.

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.

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If I recall correctly, mongo only requires that the index gets stored in memory. The actual data itself can go on disk.

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If you actually use Mongo in practice, everything needs to be in ram to have any kind of performance

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It requires neither.

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facepalm. Indices on disk is a solved problem.

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You know, I didn't think about how similar Redis and Mongo are at the core when I first read your comment. The first thing that jumped out at me was the large set of disparities.

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.

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there's something to be said for promoting an application proportionally to the maturity of its implementation. An application with a larger and more sprawling featureset would need to spend several years in "low key" mode, proving itself in production usage by a relatively low number of shops who treat it with caution. I think the issue here is one of premature overselling.

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Good point.

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