📖 The AI Tool Bible

Dataiku vs LangGraph

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Dataiku
Agents
LangGraph
Agents
TaglineEnterprise AI platform unifying data, ML, LLMs, and agents under one governed workflow.Stateful, graph-based agent orchestration from LangChain.
CategoryAgentsAgents
PricingEnterprise· Free Community edition + Cloud trial; paid tiers quote-basedFreemium· Free open-source; LangGraph Platform paid
ModelMulti-model (LLM Mesh: OpenAI, Anthropic, Bedrock, Vertex, OSS)BYO (Claude / GPT / open)
Editorial score—8.8 / 10
Use cases
enterprise-aiagent-orchestrationmlopsllm-governancedata-scienceanalytics
stateful agentshuman-in-loopproduction
Pros
  • Unifies analytics, ML, LLMs, and agents in one governed platform
  • Strong low-code surface so non-engineers can ship
  • Mature MLOps, lineage, audit, and cost controls
  • Multi-cloud and on-prem deploys; broad data connector library
  • LLM Mesh abstracts vendors with PII and policy guardrails
  • Reliable, debuggable agent graphs
  • Built-in persistence + HITL
  • Production-grade
  • Tight LangSmith integration
Cons
  • Enterprise-only pricing; no public price list
  • Heavy platform that's overkill for small teams
  • Learning curve across the visual + code surface
  • Agent tooling is newer than its ML/analytics core
  • Steeper learning curve than CrewAI
  • Verbose to set up
Websitedataiku.comwww.langchain.com
Pick Dataiku if
  • ✅ Unifies analytics, ML, LLMs, and agents in one governed platform
  • ✅ Strong low-code surface so non-engineers can ship
  • ✅ Mature MLOps, lineage, audit, and cost controls
  • ✅ Multi-cloud and on-prem deploys; broad data connector library
Pick LangGraph if
  • ✅ Reliable, debuggable agent graphs
  • ✅ Built-in persistence + HITL
  • ✅ Production-grade
  • ✅ Tight LangSmith integration
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