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by kerkeslager 3255 days ago
The problem with a feature comparison between Mongo and another database is that feature comparisons rarely include the features that Mongo lacks. Mongo looks good if you ask about sharding or replicating, but Mongo looks terrible if you ask about losing data or leaking memory. But nobody asks about losing data or leaking memory because they reasonably assume that a popular data store wouldn't do those things. That assumption, while reasonable, would be wrong.

Think of this like Maslowe's hierarchy of needs. Sharding and replication are up at the top with self-actualization stuff like job satisfaction and feeling love toward animals. Meanwhile Mongo is missing the real basic stuff, like actually keeping your data, which is down with food, water, and shelter. You might think you care about replication, but you don't care about replication when both your database servers run out of memory at the same time.
1 comments
cupcakestand 3255 days ago
> but Mongo looks terrible if you ask about losing data or leaking memory

Sorry, but this is just not true for many years now. Mongo has its warts but reading old stuff again and again feels strange and like pure hate. If your claims have some recent sources I am happy to hear them.

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nieve 3254 days ago
The list of problems goes on, but if you want really current at a local presentation a few weeks ago a user who's actually pretty positive about MongoDB reported data loss without hardware failure with what is supposedly a safe configuration. If even experienced people who like Mongo are still losing data eight years after publich release there's a problem. The claim that it's "not true for many years now" is the result of buying into PR and fanboyism.
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cupcakestand 3254 days ago
Again the same old accusations without a single source ('local presentation', of course!).
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kerkeslager 3254 days ago
February 2017: https://jepsen.io/analyses/mongodb-3-4-0-rc3

I would expect these bugs to keep occurring, because they're still approaching the development of the consensus algorithm incorrectly. Instead of formally proving correctness, they're doing something that seems right and then patching bugs when they are discovered.

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