redb VS product

I wrote redb (https://github.com/cberner/redb) using mmap, initially. However, I later removed it and switched to read()/write() with my own user space cache. I'm sure it's not as good as the OS page cache, but the difference was only 1.2-1.5x performance on the benchmarks I cared about, and the cache is less than 500 lines of code.

exposure of the redb builder functionalities.

redb has reached its 1.0 release. The file format is now gauranteed to be backward compatible, and the API is stable. I've run pretty extensive fuzz testing, but please report any bugs you encounter.

I'm just now updating the benchmarks in the readme with multi-threaded workloads :) https://github.com/cberner/redb/pull/576

redb, but that doesn't have a stable file format yet,

I also have to support web, so I'm considering a hybrid approach with a direct IndexedDB API there and something like sqlite, percy, sanakirja, or redb on native.

Nice list, but don’t forget persy, redb and sanakirja too!

check out https://github.com/cberner/redb! it is inspired by LMDB and has comparable performance, but is entirely built in rust!

Yup, the language is immature in some domains like data replication, compilation time, lifetime expressivity, not having a default async runtime and the incompatibility of all of them. But many of these domains are worked on and improved every day this is why I love this language so much. This is because there is space for improvement. I also hope that one day we will have a pure-Rust LMDB alternative that I can contribute to without fear of C.

they are, ya! I'm quite excited about that, and already have a PR open to use GATs. It's not enough to fix this issue though, because std needs to add support for LendingIterator too

We’re excited to walk our first steps toward semantic search. We can’t wait to hear your thoughts on integrating Meilisearch as a vector store. You can give your feedback in this Github discussion.

Looks good in fact! We will eventually let users use third-party API like OpenAi and Hugging Face to compute the embedding of the documents and queries. You can try our first prototype if you want.

Hey @jiripospisil,

Indeed Meilisearch does not offer an aggregation feature yet although it will be possible to get stats for the `min` and `max` values of a faceted field in the next version (v1.1)

Please tell us more about what you mean by aggregation and why it is critical for your use-case by creating a discussion on Github here (https://github.com/meilisearch/product/discussions) or by proposing a new idea on our public portal here (https://roadmap.meilisearch.com) if you don't have a Github account.

Thank you!

If you remove the URLs from indexation, it'll generally save a ton of place and will be much, much faster to index. We are thinking about not indexing URLs by default; you can help us by explaining your use case here -> https://github.com/meilisearch/product/discussions/553

Just a detail, if you're making a `du -sh` on your computer, the size on the disk will stay unchanged because we are doing soft deletion ;). Don't worry. It will be physically deleted after a while if you need it in the future.

If you kept the default configuration of Meilisearch, the maximum size of the HTTP payload is 100Mb (for security). You change it here -> https://docs.meilisearch.com/learn/configuration/instance_op...

addDocumentsInBatches() is just an helper to send your big json array into multiple parts, not absolutely sure you'll need it. (Code -> https://github.com/meilisearch/meilisearch-js/blob/807a6d827...)

I advise you to fill out a discussion on our product repository for us to evaluate your needs, and use case and then see what we plan about that.