Weaviate
Context / RAG ยท Hybrid vector + keyword search with built-in vectorization for codebase RAG
At a glance
| Setup effort | Medium |
| Released | 2019 |
| Open source | Yes |
| Hosting | Cloud |
| Privacy | Configurable |
| Update mode | On-demand |
| Staleness | manual |
| Index type | AST / Hybrid |
| Index limit | Large |
| Capabilities | Hybrid search, Embedding-based search, Vector storage, API, Native vectorizer, Multi-modal |
What Weaviate does
Hybrid search, Embedding-based search, Vector storage, API, Native vectorizer, Multi-modal
Best for
Hybrid vector + keyword search with built-in vectorization for codebase RAG
Works well with
LLM Provider / Model
Integration
Agent / Orchestration
Conflicts & caveats
- โ ๏ธ SWE-agent with on-demand context "Weaviate" may act on stale code โ prefer real-time context (Cursor @codebase, Greptile, GitHub Copilot indexing, Augment Context, CocoIndex, turbopuffer).
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