LlamaIndex

Chroma

Open-source, Apache 2.0 embedding database with a deliberately minimal 4-function API, the go-to choice for prototyping RAG apps before optionally scaling to Chroma Cloud's serverless offering.

Freemium

Databases

4/5

LlamaIndex's llama-index-vector-stores-chroma package wraps Chroma as a vector store, a frequent choice for local prototypes because Chroma runs embedded with no server.

Pinecone

A fully managed, serverless vector database that stores billions of vectors with no servers to provision, plus hosted embedding and reranking (Pinecone Inference) and a RAG toolkit (Pinecone Assistant).

Freemium

Databases

4/5

LlamaIndex's llama-index-vector-stores-pinecone package stores and queries embeddings in Pinecone, a common managed retrieval backend for LlamaIndex RAG applications.

Qdrant

An open-source vector database written in Rust, free to self-host under Apache 2.0, with a managed Qdrant Cloud that includes a free-forever cluster and hybrid and private deployment options.

Freemium

Databases

4/5

LlamaIndex's llama-index-vector-stores-qdrant package uses Qdrant as a vector store for indexes and retrievers, including hybrid dense and sparse search.

Ollama

The most widely used way to run open-weight LLMs locally — one command downloads and serves models like Llama, Qwen, DeepSeek, GLM, and MiniMax through an OpenAI-compatible API, with an optional paid Ollama Cloud tier for larger models than local hardware can handle.

Freemium

APIs & Infrastructure

3/5

LlamaIndex's llama-index-llms-ollama package points its query engines and agents at models served locally by Ollama, for RAG that stays on your own hardware.

Langfuse

Open-source platform for tracing, evaluating, and monitoring LLM applications and AI agents. It adds prompt management, datasets, and cost and latency analytics, and runs as a managed cloud or self-hosted.

Freemium

Observability & Monitoring

3/5

Langfuse traces LlamaIndex applications through an official integration, recording each retrieval, LLM call, and agent step with its cost and latency.

OpenAI

OpenAI's API platform for the GPT-6 family (Astra, Sol, Luna), Codex coding models, real-time voice, image generation, and embeddings, with tool use, structured outputs, and fine-tuning.

Usage Based

LLM

4/5

LlamaIndex's llama-index-llms-openai and embeddings packages run its query engines and agents on OpenAI models, the framework's long-standing default provider.

Python

Python is a high-level, interpreted, dynamically typed programming language emphasising readability and simplicity. It dominates data science, machine learning, and general-purpose scripting.

Open Source

Programming Languages

5/5

LlamaIndex is a Python framework for retrieval-augmented generation and document-centric agents.

JavaScript

A high-level, dynamic programming language primarily used for web development. Runs natively in browsers and on servers via Node.js, making it the most widely deployed programming language in history.

Open Source

Programming Languages

3/5

LlamaIndex.TS is the framework's TypeScript edition for JavaScript teams, trailing the Python package in features.

LangChain

Open-source Python and JavaScript framework for building LLM-powered agents and applications, with LangGraph for stateful multi-agent orchestration and LangSmith for tracing, evaluation, and deployment.

Open Source

Agentic AI

5/5

LlamaIndex and LangChain are the two most widely used LLM application frameworks. LlamaIndex goes deeper on retrieval, indexing, and document parsing; LangChain is broader on tool orchestration, integrations, and agent control flow.

Mastra

A TypeScript-native agent framework for building agents, workflows, and RAG pipelines with unified model routing, observational memory, and built-in evals. Apache 2.0 core, YC-backed.

Freemium

Agentic AI

3/5

LlamaIndex is Python-first with a TypeScript edition that trails it, and leads on document retrieval; Mastra is TypeScript-native with workflows, memory, and RAG in one framework.

OpenAI Agents SDK

OpenAI's open-source framework for building single and multi-agent applications in Python and TypeScript. It provides agents, tools, handoffs, guardrails, sessions, built-in tracing, and sandboxed execution, and works with OpenAI and 100+ other models.

Open Source

Agentic AI

3/5

The OpenAI Agents SDK focuses on agent loops, handoffs, and tool orchestration; LlamaIndex is the stronger choice when the hard part is retrieval over documents, with data connectors, indexes, and parsing built in.

LangGraph

A low-level orchestration runtime from LangChain for building stateful, multi-agent applications as graphs — nodes, edges, cyclic execution, and durable state with checkpointing, human-in-the-loop, and time travel. MIT-licensed, Python and JavaScript.

Freemium

Agentic AI

3/5

LlamaIndex Workflows is event-driven, with typed steps that emit and consume events; LangGraph models an agent as an explicit graph with checkpointed state. LlamaIndex fits retrieval-heavy agents, LangGraph fits complex tool orchestration.

CrewAI

An open-source Python framework for orchestrating role-playing autonomous AI agents into collaborating teams — MIT-licensed, standalone (no LangChain dependency), with a managed platform for deploying and monitoring agent workflows.

Freemium

Agentic AI

3/5

LlamaIndex builds agents around retrieval over documents and data connectors; CrewAI organises several role-based agents into a crew. Pick by whether the problem is finding the right data or coordinating agents.

Pydantic AI

A type-safe Python agent framework from the team behind Pydantic — applies Pydantic's validation engine to LLM interactions so structured outputs, tool arguments, and dependencies are checked at write time, with native Logfire observability.

Open Source

Agentic AI

3/5

LlamaIndex ships hundreds of data connectors, indexes, and query engines for RAG; Pydantic AI is a leaner framework focused on type-safe agents and validated outputs, leaving retrieval to you.