Table of Contents
Quick Answer
LangChain wins for general-purpose LLM apps and agents; LlamaIndex wins for advanced RAG and data-heavy workflows; Haystack wins for production-grade NLP pipelines at enterprise scale.
- Best for LLM apps & agents: LangChain + LangGraph
- Best for RAG & data ingestion: LlamaIndex
- Best for enterprise NLP pipelines: Haystack
LangChain Overview
LangChain (open source, $100M+ raised by LangChain Inc.) is the most-used LLM framework in 2027. LangChain provides chains, tools, and integrations; LangGraph adds durable agent state; LangSmith provides observability and evals. Deployed in 200K+ production apps.
LlamaIndex Overview
LlamaIndex focuses on the data side of LLM apps — ingestion, indexing, retrieval, and agents over structured and unstructured data. LlamaParse handles complex PDFs and tables; LlamaCloud offers managed services. Preferred for document-heavy RAG.
Haystack Overview
Haystack by deepset is the mature enterprise pipeline framework — production-ready from day one, with strong NLP heritage. Haystack 2.0 uses a clean component pipeline model and integrates with vector DBs, LLMs, and evaluation tools. Trusted by regulated enterprises.
Head-to-Head Comparison
| Feature | LangChain | LlamaIndex | Haystack |
|---|---|---|---|
| Agent framework | LangGraph (industry leading) | Yes | Limited |
| RAG depth | Good | Excellent | Excellent |
| Document parsing | Good | LlamaParse (excellent) | Good |
| Observability | LangSmith | Limited | Yes |
| Production maturity | Maturing | Maturing | Yes (industry leading) |
| Community size | Largest | Large | Medium |
| Language support | Python, JS | Python, TS | Python |
| Enterprise adoption | Large | Growing | Large |
Pricing Comparison
| Offering | LangChain | LlamaIndex | Haystack |
|---|---|---|---|
| Open source | Free | Free | Free |
| Hosted / Cloud | LangSmith (paid) | LlamaCloud (paid) | deepset Cloud (paid) |
| Starter | $39/mo | $50/mo | Custom |
| Enterprise | Custom | Custom | Custom |
Best For
- Building AI agents: LangChain + LangGraph
- Advanced RAG over PDFs: LlamaIndex + LlamaParse
- Enterprise NLP pipelines: Haystack
- Prototyping: LangChain — biggest ecosystem
- Data-heavy apps: LlamaIndex — deeper data abstractions
- Regulated industries: Haystack — production hardening
Our Verdict
For greenfield LLM apps in 2027, LangChain + LangGraph + LangSmith is the most complete stack. For document-heavy RAG, LlamaIndex is better optimized. For enterprise deployments requiring observability and hardening, Haystack remains a safer bet.
Conclusion
Agents → LangChain + LangGraph. Document RAG → LlamaIndex. Enterprise pipelines → Haystack. Most teams start with LangChain and add the others as they specialize.