LangChain vs Chroma
The framework for building LLM apps — chains, agents, RAG, LangGraph
vs. Open-source vector DB designed for AI apps — embeddings-first, dev-friendly
Pricing tiers
LangChain
OSS (MIT)
MIT-licensed core library. Free forever. Python + JS.
$0 base (usage-based)
LangSmith (see entry)
Observability layer — Developer free, Plus $39/seat. Separate platform.
$0 base (usage-based)
LangGraph Platform — Developer
Deploy LangGraph agents as an API. Free tier — limited execution minutes.
$0 base (usage-based)
LangGraph Platform — Plus
$39/seat/mo (tied to LangSmith Plus). More execution credit. Production features.
$39/mo
Enterprise
Custom. Self-host, dedicated support, SSO.
Custom
Chroma
Cloud — Free
$5 free credits. Great for trying it out.
Free
Cloud — Pro
$100 credits included, then usage-based. Dedicated resources, SOC2, priority support.
$0 base (usage-based)
Self-Host (OSS)
MIT-licensed. Embedded or Docker. Free forever.
$0 base (usage-based)
Cloud — Enterprise
Custom. VPC, compliance, dedicated support.
Custom
Free-tier quotas head-to-head
Comparing oss on LangChain vs cloud-free on Chroma.
| Metric | LangChain | Chroma |
|---|---|---|
| No overlapping quota metrics for these tiers. | ||
Features
LangChain · 18 features
- Agents — Tool-using agents with reasoning loops.
- Chains (LCEL) — LangChain Expression Language — pipe primitives into chains.
- Checkpointers (LangGraph) — Persist agent state to SQL, Mongo, Redis, Postgres.
- Document Loaders — 150+ loaders for PDF, HTML, Notion, Google Drive, S3, GitHub, etc.
- Human-in-the-loop — Pause agent for approval, then resume.
- LangGraph — Stateful graph-based agent runtime. Durable, replayable, human-in-the-loop.
- LangGraph Platform — Managed hosting for LangGraph agents with state persistence.
- LangGraph Studio — Desktop IDE for debugging agent graphs.
- LangServe — Deploy chains as FastAPI endpoints.
- Memory — Buffer, summary, entity, vector memory stores.
- Output Parsers — Structured JSON, Pydantic schemas, function calling.
- Prompt Templates — Templating + partial filling + output parsers.
- RAG (Retrieval-Augmented Generation) — Standard patterns + 50+ retrievers.
- Streaming — First-class streaming at every layer.
- Subgraphs — Compose agent graphs hierarchically.
- Text Splitters — Recursive, token, semantic splitters for chunking.
- Tools — 400+ pre-built tools (web search, code, databases, APIs).
- Vector Store Integrations — 60+ vector DBs (Pinecone, Chroma, Weaviate, PGVector, Qdrant, Milvus).
Chroma · 11 features
- Client-Server Mode — Run Chroma via Docker; clients connect over HTTP.
- Collections — Named groups of embeddings + metadata.
- Distributed (Cloud) — Horizontal scaling on Chroma Cloud.
- Embedded Mode — In-process Python — chromadb.Client() and go. Zero setup.
- Embedding Functions — Plug-in embedders (OpenAI, Cohere, SentenceTransformers, HF).
- Full-Text Search — BM25 + vector hybrid.
- Metadata Filters — Where-clause query language.
- Migration Tools — Import from Pinecone + other stores.
- Multi-Modal — Text + image embeddings (CLIP, etc.).
- Python + JS APIs — Same API shape across both SDKs.
- Serverless Cloud — Pay for storage + queries, auto-scale.
Developer interfaces
| Kind | LangChain | Chroma |
|---|---|---|
| SDK | @langchain/core (Node), langchain (Python), langgraph (JS), langgraph (Python), LangServe | chromadb (JS/TS), chromadb (Python) |
| REST | LangGraph Platform | Chroma HTTP API |
| MCP | — | Chroma MCP |
| OTHER | — | Docker Server, Embedded Mode (in-process Python) |
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