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This one is for the hardcore techies in the audience. Does anybody have any *practical* experience with the NoSQL world? Querki doesn't fit the traditional SQL mold very well, so I'm comparing NoSQL options -- in particular, document-centric data stores, which are broadly the best match for our needs. So far, three options look particularly intriguing:
  • MongoDB -- very fast, a tad unreliable architecturally, lots of query power

  • CouchDB -- super-reliable by design

  • Postgres with hstore -- today's discovery (which prompted this question), which lets you mix traditional columns with key-value bags
I haven't worked with any of them, and trying to find unbiased info about the gotchas and performance tradeoffs online is frustrating. (And StackOverflow tends to frown on this sort of "who's better?" question.)

So any and all informed opinions about these or similar options would be greatly welcomed. Thanks...

(no subject)

Date: 2012-10-25 02:38 pm (UTC)
From: [identity profile] goldsquare.livejournal.com
Isn't there also an open source distributed database that Google uses internally, and which they have released?

Largely I'm a SQL and tongs kind of guy. :-)

(no subject)

Date: 2012-10-25 06:21 pm (UTC)
From: [identity profile] marphod.livejournal.com
While the user-level data may not be relational in the way SQL wants (and I'd posit that that is only true of some of the user-level data), certainly the back-end data is. Users, settings, and user groups, access rights and owned objects, external references, and the like.

The big advantage of MongoDB and CouchDB over traditional SQL is speed, speed, and speed. This begs the question; how important is speed to Querki? I may be wrong, but at least in the initial stages, it doesn't seem to be as necessary.

(Also, assuming you put an abstraction layer over the DB backend, switching DBs shouldn't be that hard.)

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