Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.
Awadb
AwaDB provides an AI-focused embedding vector database with real-time search features.

About Awadb
AwaDB is an open-source, AI-native database for embedding vectors. It is distributed as a GitHub repository and can run as a local Python library on macOS or Linux, or as a service via Docker for Windows or other service deployments. It supports Python and RESTful usage, requires no manual schema definition or vector index tuning, and uses a lock-free realtime index with millisecond-level latency. Sentences are embedded with Sentence Transformers by default; users can also supply embeddings from OpenAI or other LLMs.
Key features
- Stores and searches embedding vectors for AI applications.
- Requires no manual schema definition or vector index tuning.
- Uses a lock-free realtime index with millisecond-level latency.
- Runs locally via pip on macOS or Linux.
- Deploys as a Docker service, including for Windows.
- Offers Python client and RESTful API; defaults to Sentence Transformers embeddings.
- Open source and distributed through GitHub.
- No schema or vector indexing details required for basic use.
- Based on over five years of production experience with Vearch.
- Local Python library installation is described for macOS or Linux; Windows users are directed to Docker.
- Service use requires downloading and deploying the Docker container yourself.
Awadb at a glance
- Website
- github.com/awa-ai/awadb
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Platforms
- Linux
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Awadb FAQ
How do I install AwaDB for local Python use?
Can AwaDB use embeddings from OpenAI or other LLMs?
Does AwaDB expose a REST API?
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