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
| Attribute | txtai | Weaviate |
|---|---|---|
| Category | Vector DB | Vector DB |
| Pricing (differs) | FREE | FREEMIUM |
| License (differs) | Open source | Open core |
| Deployment (differs) | Self-host | Hybrid |
| Platforms (differs) | API, CLI | API |
| Model support | Model-agnostic | Model-agnostic |
| Vendor (differs) | NeuML | Weaviate |
| Capabilities (differs) |
|
|
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
When to pick which
Across the signals we compare, txtai and Weaviate differ on pricing, license, deployment, and platforms:
- Pricing
- FREE · FREEMIUM
- License
- Open source · Open core
- Deployment
- Self-host · Hybrid
- Platforms
- API, CLI · API
Their capability lists differ in recorded depth — compare the full lists above before deciding.