Announcing Hybrid Search Support for LlamaIndex
Blog post from MongoDB
MongoDB has announced enhancements to their LlamaIndex integration, combining robust database capabilities with LlamaIndex's innovative context-augmented large language models (LLMs). The enhanced integration supports vector search, full-text search, and hybrid search, enabling developers to create more context-aware applications. LlamaIndex is a leading AI framework for building with LLMs, streamlining the integration of external data sources and allowing developers to combine LLMs with relevant context from various data formats. MongoDB's LlamaIndex integration supports customizable storage components, enabling developers to leverage MongoDB Atlas as a powerful vector store and key-value store. The integration also simplifies the implementation of hybrid search by combining full-text search with vector search for precise and user-oriented results.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 9 | 4,605 | 291 | 90 | +25% |
| RAG | 4 | 2,177 | 276 | 82 | +12% |
| LLM | 3 | 3,598 | 465 | 143 | -7% |
| Data Pipeline | 2 | 720 | 225 | 62 | -49% |
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