Show HN: HelixDB – Open-source vector-graph database for AI applications (Rust)

there is also the fact that the more dimensions you have for embedded data the more diluted the embedding becomes so it is unusual to go anywhere near the limits of vector length!

SPALDE*

Hey George, Alexander from SurrealDB here.

Congratulations on the launch! This is a very exciting space, and it's great to see your take on it.

Running fair benchmarks, not benchmarketing, is a significant effort and we recently put in this effort to make things as fair and transparent as possible across a range of databases.

You can see the results and links to our code in the write-up here: https://surrealdb.com/blog/beginning-our-benchmarking-journe...

We'd be very interested in seeing the benchmarks you'd run and how we compare :)

You can sacrifice many things for faster performance, such as security, consistency levels or referential integrity.

I'm genuinely curious to learn what design decisions you will make as you continue building the database. There are so many options, each with its pros and cons.

If you would like to have a chat where we can exchange ideas, happy to do that :)

This is very cool, and right up my alley. Hesitant to try it out because of the bespoke query language for now.

I wonder if you'd like to share your thoughts on GQL becoming an ISO standard? Also, have you looked into how Neptune Analytics handles vector embeddings?

> In-house graph-vector storage engine (to replace LMDB)

Not sure if it's possible. But why not use fjall, if it is? [0]

[0]: https://github.com/fjall-rs/fjall/