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#xtdb
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2023-09-12
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refset22:09:36

πŸ“£ https://github.com/xtdb/xtdb/releases/tag/1.24.1 is out! There's really only a few bug fixes in this minor release (see the release notes linked for details), but hopefully they unblock a few people πŸ™‚ thanks as ever to everyone who helps us with these releases by reporting issues and testing fixes πŸ™

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jarohen22:09:16

I do, but I suspect they might be discounted for bias πŸ˜‡

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tatut05:09:23

appropriate meme, we are spoiled for choice to have 2 good datalog-like systems to choose from

otfrom07:09:50

@U050V1N74 I suppose I'd be interested to know when you would consider datomic to be a better fit for the problem.

littleli07:09:48

xtdb makes a case even outside the world of Clojure. Java apis are familiar and easy to use. I cannot use Clojure at work 😒 I can use Java :saluting_face:

jarohen07:09:06

@U0525KG62 they both target very similar use cases, so it's likely that if one's suitable for a particular problem/domain, broadly speaking, the other will be too. Functionally, beyond bitemporality, it's down to personal preferences - whether you prefer documents or triples, your opinions on schema etc. Openly, familiarity within the team/company with one or the other, both in development and operationally, is likely to outweigh any single feature. Performance is also an important factor - as always, worth measuring for the individual use case. tl;dr "it depends", but I'm guessing that's not what you were looking for πŸ™‚

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otfrom07:09:54

gives me an idea of what some of the things in "it depends" are.

otfrom07:09:04

for my use case (a datalog that I can use for a personal knowledge management system on a single machine) I think that datahike might work best for me b/c it is pretty easy to get going, but then it has been a good long while since I looked at what was needed to get a basic single user xtdb going

otfrom07:09:10

and for work what I really want are just flat files and parquet and arrow are good for that (and we're looking at duckdb for some things), but all of that is analysing data using tech.ml.dataset and friends