OctoSQL[0] or DuckDB[1] will most likely be much simpler, while going through 10 GB of JSON in a couple seconds at most. Disclaimer: author of OctoSQL [0]: https://github.com/cube2222/octosql. - Source: Hacker News / over 1 year ago

This is really cool! With their Postgres scanner[0] you can now easily query multiple datasources using SQL and join between them (i.e. Postgres table with JSON file). Something I strived to build with OctoSQL[1] before. It's amazing to see how quickly DuckDB is adding new features. Not a huge fan of C++, which is right now used for authoring extensions, it'd be really cool if somebody implemented a Rust extension... - Source: Hacker News / over 1 year ago

Congrats on the Show HN! It's great to see more tools in this area (querying data from various sources in-place) and the Lambda use case is a really cool idea! I've recently done a bunch of benchmarking, including ClickHouse Local and the usage was straightforward, with everything working as it's supposed to. Just to comment on the performance area though, one area I think ClickHouse could still possibly improve... - Source: Hacker News / over 1 year ago

SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions! As far as similar tools go, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2]. DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats. Dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath... - Source: Hacker News / over 1 year ago

To add somewhat of a counterpoint to the other response, I've tried the Steampipe CSV plugin and got 50x slower performance vs OctoSQL[0], which is itself 5x slower than something like DataFusion[1]. The CSV plugin doesn't contact any external API's so it should be a good benchmark of the plugin architecture, though it might just not be optimized yet. That said, I don't imagine this ever being a bottleneck for the... - Source: Hacker News / over 1 year ago

In my usual NodeJS tech stack, which includes GraphQL, NestJS, SQL (predominantly PostgreSQL with MikroORM), I encountered these limitations. To overcome them, I've developed a new stack utilizing Rust, which still offers some ease of development:. - Source: dev.to / 9 months ago

Mikro-ORM is a TypeScript ORM that focuses on simplicity and efficiency. It supports various SQL databases and MongoDB. Mikro-ORM is known for its simplicity and developer-friendly APIs. It provides a concise syntax for defining data models and relationships, making it easy to use. - Source: dev.to / 9 months ago

I found MikroORM [0] to be quite reasonable if you're in the TS ecosystem already. It was also easy to do custom, raw queries, and really just felt like it wasn't in the way. [0] https://mikro-orm.io/. - Source: Hacker News / 9 months ago

It also does code generation into its own module, so good luck with hoisting in a monorepo where you want multiple independent prisma schemas. MikroORM[1] is a much better alternative to Prisma in my opinion but any ORM carries some form of baggage. [1] https://mikro-orm.io/. - Source: Hacker News / about 1 year ago

I recommend looking at https://mikro-orm.io/. Source: over 1 year ago