Multi Index Data Structure With Query Engine Abstraction

via “multi-index query orchestration with hybrid retrieval strategies”

LlamaIndex is the leading document agent and OCR platform

Unique: Implements composable QueryEngine routers that can combine vector, keyword, graph, and structured queries through a unified interface with pluggable result merging strategies. Unlike LangChain's retriever composition (which chains retrievers sequentially), LlamaIndex's QueryEngine supports parallel multi-index querying with configurable fusion algorithms.

vs others: Enables true hybrid search with automatic result normalization and ranking, whereas LangChain requires manual result merging and score normalization across different retriever types.

via “multi-index data structure with query engine abstraction”

Interface between LLMs and your data

Unique: Supports 5+ index types with pluggable backends and a unified QueryEngine abstraction, enabling seamless switching between retrieval strategies (semantic, keyword, graph traversal, summarization) without rewriting application code. Implements automatic index persistence and lazy loading.

vs others: More flexible than LangChain's VectorStore abstraction by supporting multiple index types (graph, keyword, summary) with unified query interface; enables hybrid retrieval combining multiple strategies in a single query.

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