Elasticsearch (Vector)
Context / RAG · Adding vector search to existing Elastic deployments with hybrid BM25 + ANN
At a glance
| Setup effort | Medium |
| Released | 2010 (vector since 2022) |
| Open source | Yes |
| Hosting | Both |
| Privacy | Configurable |
| Update mode | Real-time |
| Staleness | manual |
| Index type | Embeddings + BM25 |
| Index limit | Very large |
| Capabilities | Embedding search, BM25, Hybrid search, kNN, ELSER sparse embeddings, ESQL |
What Elasticsearch (Vector) does
Embedding search, BM25, Hybrid search, kNN, ELSER sparse embeddings, ESQL
Best for
Adding vector search to existing Elastic deployments with hybrid BM25 + ANN
Works well with
LLM Provider / Model
Integration
Agent / Orchestration
Conflicts & caveats
- ⚠️ SWE-agent with on-demand context "Elasticsearch (Vector)" may act on stale code — prefer real-time context (Cursor @codebase, Greptile, GitHub Copilot indexing, Augment Context, CocoIndex, turbopuffer).
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