LlamaIndex

LlamaIndex is a data framework for building LLM applications that need to ingest, structure, and query custom data. While LangChain provides general-purpose LLM application building blocks, LlamaIndex focuses specifically on the data layer — making it the go-to framework for RAG systems, knowledge bases, and any application where Claude needs to reference specific documents or datasets.

LlamaIndex's architecture is built around the concept of 'indexes' — data structures that organize your documents in ways that make them efficiently queryable by language models. The framework supports dozens of index types (vector, keyword, tree, graph) and includes connectors for hundreds of data sources (PDFs, databases, APIs, wikis, Slack, Google Drive, and more).

The framework's 'query engine' abstraction handles the complex orchestration of retrieval, reranking, and response synthesis that production RAG systems require. This abstraction layer means developers can switch between different retrieval strategies, embedding models, and language models without rewriting their application code.