Omendb

What it is

Omendb is a fast, embedded vector database that uses HNSW and ACORN-1 for efficient filtered searches. It's ideal for applications requiring quick retrieval of high-dimensional data.

Omendb stands out as an efficient and fast embedded vector database, offering a lightweight solution for high-dimensional data retrieval with HNSW and ACORN-1.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited language support beyond JavaScript/TypeScript

   Primary support is for JavaScript and TypeScript, with no official SDKs or libraries for other languages.

2. 02

   Documentation lacks depth and examples

   The documentation provides basic setup instructions but lacks advanced usage scenarios and detailed API descriptions.

3. 03

   Performance degradation with very large datasets

   Benchmarking shows significant slowdowns when the dataset exceeds 1 million vectors, despite optimizations for high-dimensional data retrieval.

4. 04

   Small and less active community

   GitHub repository has minimal contributions from external developers and limited activity in issue tracking and pull requests.

What it does well

• Fast embedded vector database

• Uses HNSW for efficient search

• ACORN-1 for filtered searches

• Optimized for high-dimensional data retrieval

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.