Llamaindex Document Indexing And Retrieval With Multi Format Support

via “multi-strategy document indexing with pluggable index types”

Data framework for LLM applications — advanced RAG, indexing, and data connectors.

Unique: Unified abstraction across four distinct index types (vector, keyword, tree, knowledge graph) with pluggable storage backends, allowing users to compose retrieval strategies without rewriting core logic. The property graph index specifically enables structured entity/relationship queries alongside semantic search.

vs others: More flexible than Langchain's basic vector store abstractions because it natively supports multiple index types and graph-based retrieval; more opinionated than raw vector DB SDKs because it handles document parsing, chunking, and index orchestration automatically.