LangChain vs LlamaIndex: Engineer’s Field Guide
RAG frameworksSeptember 11, 2025
7 min read
LangChain vs LlamaIndex: Engineer’s Field Guide
Last reviewed: 2025-09-11.
Executive summary
- Both are open-source RAG frameworks under MIT licenses. LangChain and LangGraph are MIT-licensed; LlamaIndex is MIT-licensed. (LangChain LICENSE) (LangGraph LICENSE) (LlamaIndex LICENSE).
- Orchestration model differs. LangChain provides LCEL for chains and recommends LangGraph for complex state, branching, cycles, or multi-agent workflows (LCEL doc: “recommend … LangGraph”). LlamaIndex offers Workflows and Agents for event-driven pipelines (Workflows doc).
- Data connectivity is broad in both. LangChain exposes hundreds of document loaders and many vector-store integrations (Loaders index) (Vector stores, Python) (Vector stores, JS). LlamaIndex curates connectors via LlamaHub and supports many vector stores (LlamaHub) (LlamaIndex vector stores).
- Managed options. LangChain offers LangSmith (observability & evals) and LangGraph Platform; pricing/limits and EU/US regions are published (as of 2025-09-11). (LangChain Pricing & Plans). LlamaIndex offers LlamaCloud (managed parsing/ingestion/retrieval) and LlamaParse with credit-based pricing (as of 2025-09-11). (LlamaCloud Credit Pricing & Usage) (LlamaParse FAQ).
- Security & residency. LlamaCloud states GDPR adherence, SOC 2 Type 2 and HIPAA, with data stored/processed in the selected region (EU or NA) (as of 2025-09-11). (LlamaCloud Regions & Compliance). LangChain offers EU data residency for LangSmith and states “We will not train on your data.” (as of 2025-09-11). (EU residency announcement) (LangSmith Pricing FAQ).
TL;DR — When to choose which
- Choose LangChain if…
- You need stateful, multi-actor agents with human-in-the-loop and persistence via LangGraph. (LangGraph concepts).
- You want first-party tracing & evaluations (online and offline) via LangSmith. (LangSmith online evaluations) (Evaluation overview).
- You prefer broad integrations for loaders and vector stores across Python and JS. (Loaders) (Vector stores, Py) (Vector stores, JS).
- You plan to expose chains as REST quickly via LangServe. (LangServe docs).
- Choose LlamaIndex if…
- You need turnkey parsing of complex documents; LlamaParse caches files for 48 hours and then permanently deletes them (as of 2025-09-11). (LlamaParse FAQ) (Cache options).
- You want OpenTelemetry-native observability that exports to common backends (Jaeger/Zipkin/Prometheus). (Observability / OpenTelemetry).
- You value a connector catalog (SaaS/DBs/files) via LlamaHub and managed indices in LlamaCloud. (LlamaHub) (LlamaCloud Index + Retriever).
- You prefer workflow-style orchestration and LlamaDeploy for serving. (Workflows guide) (LlamaDeploy).
What they are
LangChain. A Python/JS framework for composing LLM apps, featuring LCEL for chains and LangGraph for stateful/agentic workflows; integrates with LangSmith for tracing/evals. (LCEL concept) (LangGraph docs) (LangSmith overview).
LlamaIndex. A data framework for RAG that provides loaders, indices, query engines, agents/workflows, and managed services (LlamaCloud/LlamaParse). (Indexing overview) (Query Engine) (LlamaCloud docs).
Feature comparison
| Capability | LangChain | LlamaIndex |
|---|---|---|
| Core orchestration | LCEL for chains; LangGraph for stateful/agentic flows; LCEL docs recommend LangGraph for complex state/branching. (LCEL doc) (LangGraph concepts). | Workflows & Agents abstractions for event-driven pipelines. (Workflows). |
| Data connectors | Broad catalog of document loaders. (Loaders index). | LlamaHub catalog of readers/tools/packs. (LlamaHub). |
| Vector stores | Many stores across Python and JS. (Vector stores, Py) (Vector stores, JS). | Numerous vector stores supported. (LlamaIndex vector stores). |
| Managed services | LangSmith (tracing/evals); LangGraph Platform for deploying agents with published limits and EU/US regions (as of 2025-09-11). (LangChain Pricing & Plans). | LlamaCloud (managed parsing/ingestion/retrieval) and LlamaParse (credit-based) (as of 2025-09-11). (Credit Pricing & Usage). |
| Deployment | LangServe to expose chains via REST. (LangServe docs). | LlamaDeploy for deploying/serving pipelines. (LlamaDeploy). |
| Observability & evals | LangSmith provides tracing and online/offline evaluations. (Online evaluations) (Evaluation overview). | OpenTelemetry integration for tracing; evaluation modules available. (Observability / OpenTelemetry) (Evaluation docs). |
Performance & limits
- Framework throughput/latency: Neither project publishes standardized performance numbers for the OSS libraries. Undisclosed by vendor (as of 2025-09-11).
- Managed limits (examples): LangChain’s pricing table documents trace retention (Base 14 days; Extended 400 days) and published rate limits such as “Max ingested events/hour” (as of 2025-09-11). (LangChain Pricing & Plans).
- Data retention: LlamaParse caches files 48 hours before permanent deletion; files are used only to return results and not for model training (as of 2025-09-11). (LlamaParse FAQ) (Cache options).
- How to evaluate: Both provide first-party guides—LangSmith’s RAG evaluation tutorial, and LlamaIndex evaluation docs. (LangSmith: Evaluate a RAG app) (LlamaIndex evaluation).
Pricing & licensing
- LangChain (managed): Public pricing for LangSmith and LangGraph Platform (seats, usage tiers, retention options, EU/US data location) is documented (as of 2025-09-11). OSS LangChain/LangGraph are MIT-licensed. (LangChain Pricing & Plans) (LangChain LICENSE) (LangGraph LICENSE).
- LlamaIndex (managed): LlamaCloud/LlamaParse use credit-based pricing; region pricing varies (e.g., NA vs EU) (as of 2025-09-11). Library is MIT-licensed. (Credit Pricing & Usage) (LlamaIndex LICENSE).
Security, compliance & data handling
- LangChain / LangSmith: EU data residency option; statement that they will not train on your data and you retain ownership (as of 2025-09-11). (EU residency announcement) (LangSmith Pricing FAQ) (LangChain Pricing & Plans).
- LlamaIndex / LlamaCloud: GDPR adherence and SOC 2 Type 2 & HIPAA stated; data remains in the selected region (NA or EU); BAAs for Enterprise (as of 2025-09-11). (LlamaCloud Regions & Compliance).
- LlamaParse retention: Files cached 48 hours, then deleted; not used for model training (as of 2025-09-11). (LlamaParse FAQ).
Ecosystem & integrations
- LangChain: Extensive document loaders and vector-store integrations across Python and JS. (Loaders) (Vector stores, Py) (Vector stores, JS).
- LlamaIndex: LlamaHub provides many ready-to-use connectors/tools; LlamaIndex supports numerous vector stores and managed indices in LlamaCloud. (LlamaHub) (Vector stores) (Managed indices docs).
Developer experience
- LangChain: Start with LCEL for simple chains; move to LangGraph for complex state/agents. Built-in deployment via LangServe; comprehensive concepts and tutorials (as of 2025-09-11). (LCEL concept) (LangGraph docs) (LangServe docs) (LangChain concepts).
- LlamaIndex: Clear building blocks for Indexing, Query Engine, and Workflows; LlamaDeploy for serving; OTEL-based tracing for observability (as of 2025-09-11). (Indexing overview) (Query Engine) (Workflows) (LlamaDeploy) (Observability / OpenTelemetry).
Decision matrix
| Scenario | LangChain | LlamaIndex | Notes |
|---|---|---|---|
| Agentic workflows with branching/loops | Strong via LangGraph | Workflows/Agents available | LCEL docs recommend LangGraph when you need complex state/branching. (LCEL doc). |
| Rapid REST exposure of chains | LangServe | LlamaDeploy | Both provide serving; LangServe integrates with FastAPI. (LangServe docs) (LlamaDeploy). |
| Observability & evals out-of-the-box | LangSmith (tracing + online/offline evals) | OTEL tracing + eval modules | LangSmith evaluation docs; LlamaIndex OTEL integration. (LangSmith evaluations) (Observability / OpenTelemetry). |
| Heavy document parsing (complex PDFs) | Via community/partner loaders | LlamaParse with 48h cache & deletion | LlamaParse retention and usage policy. (LlamaParse FAQ). |
| Broad ready-made connectors | Many loaders & stores | LlamaHub catalog | Choose based on your exact sources. (LangChain loaders) (LlamaHub). |
| Strict residency/compliance needs | EU/US data location options | SOC 2 Type 2, HIPAA, GDPR; EU/US regions | Verify BAAs & DPAs with vendor (Enterprise). (LangChain Pricing & Plans) (LlamaCloud Regions & Compliance). |
FAQs
Can I use these without any managed services?
Yes—both offer open-source libraries that you can self-host (as of 2025-09-11). (LangGraph docs) (LlamaIndex docs).Do they support many vector stores?
Yes. Each exposes a unified vector-store interface with many integrations. (LangChain vector stores, Py) (LlamaIndex vector stores).How do I deploy quickly?
Expose LangChain runnables using LangServe; deploy LlamaIndex pipelines with LlamaDeploy. (LangServe docs) (LlamaDeploy).What’s the pricing model?
LangChain publishes seat/usage pricing and retention tiers for LangSmith/LangGraph Platform (as of 2025-09-11). LlamaIndex uses credit-based pricing for LlamaCloud/LlamaParse with regional rates (as of 2025-09-11). (LangChain Pricing & Plans) (Credit Pricing & Usage).Do these platforms train on my data?
LangChain: “We will not train on your data.” (as of 2025-09-11). LlamaParse: files are used only to return results and never for model training; cached for 48h (as of 2025-09-11). (LangSmith Pricing FAQ) (LlamaParse FAQ).How do I evaluate my RAG pipeline?
Use LangSmith’s RAG evaluation workflow or LlamaIndex’s evaluation guides. (LangSmith RAG eval tutorial) (LlamaIndex evaluation).
Changelog & methodology
- Methodology: Facts in this guide were verified against primary vendor documentation, GitHub LICENSE files, and official pricing/compliance pages (links inline). When vendors do not publish standardized performance metrics, we mark them Undisclosed by vendor and point to evaluation guidance.
- Currency: Pricing, limits, certifications, and regions may change. All such claims include (as of 2025-09-11) and deep links to vendor pages for verification.