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What about a highly-structured ACID datastore designed primarily for short transactions reading & mutating small sets of random rows makes you think that? Log data is semi-structured and very heterogenous. I would choose the filesystem far before an RDBMS.

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Maybe RDBMS isn't the /most/ efficient way to store the data, but the advantage of being able to write simple and powerful queries against that data is huge. I seem to lose that with file or key/value based storage. Am I wrong? (not trying to criticize, I am genuinely curious)

Also, I don't need to worry about files across servers and rolling log files that file logs usually entail.

I'm not suggesting that a K/V store is better, just that an RDBMS isn't a good solution to this problem either. How do you effectively utilize the query capabilities of an RDBMS with semi-structured data? You're better off sticking the data in a flat file and using text processing tools to work with it.

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