txtai vs Weaviate
A side-by-side comparison of txtai and Weaviate, two Vector DB tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
At a glance
The honest brief
txtai
Unlike pure vector stores, it fuses dense + sparse vectors, graph networks, and a SQL database into a single embeddings DB.
- Fully open source (Apache-2.0), runs locally
- Vector + graph + SQL in one store
- Build with Python or YAML
- API bindings for JS, Java, Rust, Go
- Built-in RAG, agents, and pipelines
- Maintained by a small team, not a big vendor
- Smaller ecosystem than Pinecone/Weaviate
- No managed cloud offering
- More concepts than a plain vector DB
Weaviate
Built-in vectorizer modules embed text inline — raw text in, vectors out — so you skip running a separate embedding pipeline.
- Hybrid BM25 + vector search
- Self-hostable or managed cloud
- GraphQL and REST APIs
- Resource-heavy at large scale
- Module config has a learning curve
- Managed tier costs add up
- Newer than some lexical engines