txtai vs Weaviate
No clear leader: Weaviate (62.5) and txtai (61.2) are within the 5-point margin; treat as a tie. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.
Capabilities
Feature-by-feature on the axes that matter for vector databases. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
txtai
txtai is an open-source Python framework for building semantic search applications, LLM-powered agents, retrieval augmented generation systems, and language model workflows with support for multiple vector backends and integration with various LLMs.
Weaviate
A vector database that enables semantic search by storing both objects and vectors, with built-in support for combining vector similarity search with traditional keyword search, retrieval-augmented generation, and reranking capabilities.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
txtai
- llama.cpp
- LiteLLM
- Hugging Face
- OpenAI
- Claude
- AWS Bedrock
- smolagents
- OpenCode
- DuckDB
- Milvus
- LiteRT
- Model Context Protocol
Weaviate
Not documented yet.
txtai or Weaviate: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.