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I have, and there's a set of microbenchmarks in the repository. There are two links to reports on that page -- one that's executed on GitHub Actions, which can have quite widely varying performance, and one that's executed on a "dedicated" VPS instance from Scaleway -- exact specs are on that page. I've kicked off another run on that VPS, since it hasn't been run since October. It takes a while to run, so if it still says October, try hitting refresh a little later.
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BonsaiDb: An offline or networked database which offers a key-value store in addition to ACID-compliant document storage. Requires using tokio.
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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PickleDB
PickleDB-rs is a lightweight and simple key-value store. It is a Rust version for Python's PickleDB
I would think one that is based on Serde, like PickleDB, could be a good choice.
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Redis
Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.
If you need distributed access then redis
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I have two solutions I've been working on and thinking about. The first is a way to manage multiple formats of data stored in the database, by offering a way to transition old versions to the current version. A possible benefit of this approach is that it doesn't require rewriting your data at the time of schema migration. Some users may not want that extra cost (if there is any), and would prefer a way to update the data.
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CodiumAI
TestGPT | Generating meaningful tests for busy devs. Get non-trivial tests (and trivial, too!) suggested right inside your IDE, so you can code smart, create more value, and stay confident when you push.
