Marqo
Context / RAG · End-to-end vector search with built-in embedding generation and tensor pipelines
At a glance
| Setup effort | Low |
| Released | 2022 |
| Open source | Yes |
| Hosting | Both |
| Privacy | Configurable |
| Update mode | On-demand |
| Staleness | manual |
| Index type | Embeddings + Hybrid |
| Index limit | Large |
| Capabilities | Embedding search, Built-in embedding models, Multi-modal, Tensor pipelines, Hybrid |
What Marqo does
Embedding search, Built-in embedding models, Multi-modal, Tensor pipelines, Hybrid
Best for
End-to-end vector search with built-in embedding generation and tensor pipelines
Works well with
LLM Provider / Model
Integration
Agent / Orchestration
Conflicts & caveats
- ⚠️ SWE-agent with on-demand context "Marqo" may act on stale code — prefer real-time context (Cursor @codebase, Greptile, GitHub Copilot indexing, Augment Context, CocoIndex, turbopuffer).
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