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bitbonk

SpacetimeDB is an interesting new type of relational database that I haven't quite wrapped my head around yet.

It is designed for real time massive multiplayer games and uses some sort event sourcing (CRDTs?) but has many more potential use cases than just games.

It works particularly well with .NET and C#. So I have cleaned up and simplified the C# quickstart sample.

github.com/bitbonk/spacetime-q

A quickstart chat demo for SpacetimeDB. Contribute to bitbonk/spacetime-quickstart-chat development by creating an account on GitHub.
GitHubGitHub - bitbonk/spacetime-quickstart-chat: A quickstart chat demo for SpacetimeDBA quickstart chat demo for SpacetimeDB. Contribute to bitbonk/spacetime-quickstart-chat development by creating an account on GitHub.
#spacetimedb#sql#dotnet
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JavaJobs
Caching in Java with JOOQ and Redis Database caching is, to the say the least, a difficult proble...

http://logicx24.github.io/caching-with-jooq-and-redis/

#java #redis #jooq #sql #cache #database #queries #postgres #redshift

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The Sopranos, Silicon Valley, and Summer Afternoons · Caching in Java with JOOQ and RedisDatabase caching is, to the say the least, a difficult problem. Part of this is technical: making a finely-grained cache can take a lot of work, and requires a bit of creativity. But a cache is a performance optimization, and so, the main challenge is evaluating your use case, and creating a system that is optimal for your own needs.In this article, I’ll be describing how to design and code a basic, table-level cache for SQL queries. Not everyone needs this. For a lot of applications, a simple, service-level cache could suffice, and would save a lot of work and future complication. This was my first project at my current internship (at Natero, check us out), and our usage patterns demanded a cache that would be keyed by queries and would store result objects that we could easily retrieve. These jobs mainly are used to calculate the many metrics we offer, as a customer success company, and our customers use these metrics to make major business decisions, so the cache also had to always be current. There couldn’t be any latency in syncing writes.
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