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📖 The AI Tool Bible

Dataiku vs H2O.ai

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

Dataiku logo
Dataiku
Agents
H2O.ai logo
H2O.ai
Agents
Tagline
Dataiku
Enterprise AI platform unifying data, ML, LLMs, and agents under one governed workflow.
H2O.ai
Enterprise AI platform combining AutoML, generative AI, and vertical agents for regulated industries.
Pricing
Dataiku
Enterprise· Basic: $10 · Pro: $20 · Enterprise: Contact sales
H2O.ai
Enterprise· Contact sales; live demo on request
Lowest paid tier
Dataiku
$10 · Basic
captured 2026-08-10
H2O.ai
—
Free trial
Dataiku
Yes
H2O.ai
Not listed
API
Dataiku
Yes
H2O.ai
Yes
Platforms
Dataiku
api
H2O.ai
api
Open source
Dataiku
Not listed
H2O.ai
Yes
Model used
Dataiku
Multi-model (LLM Mesh: OpenAI, Anthropic, Bedrock, Vertex, OSS)
H2O.ai
Multi-model
Best for
Dataiku
Pick Dataiku if you're a large org that wants one governed platform for ML, analytics, LLMs, and agents instead of stitching five vendors together.
H2O.ai
Pick H2O.ai if you're a regulated enterprise that needs AutoML, RAG, and agents on private or air-gapped data with FedRAMP-grade controls.
Not for
Dataiku
Skip it if you're an indie dev or startup looking for a self-serve agent builder with transparent monthly pricing.
H2O.ai
Skip it if you're an indie developer or startup looking for a self-serve API and transparent per-token pricing.
Editorial score
Dataiku
8.3 / 10
H2O.ai
8.3 / 10
Use cases
Dataiku
enterprise-aiagent-orchestrationmlopsllm-governancedata-scienceanalytics
H2O.ai
enterprise-agentsautomldocument-aillm-fine-tuningfraud-detectionpredictive-analytics
Pros
Dataiku
  • 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
H2O.ai
  • Covers predictive ML and generative AI in one platform
  • Air-gapped and FedRAMP-ready deployment options
  • H2O-3 core is genuinely open source
  • Vertical agents for banking, telecom, and public sector
  • Strong AutoML pedigree with Driverless AI
Cons
Dataiku
  • 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
H2O.ai
  • No public pricing; sales-led enterprise motion
  • Overkill for individual developers or small teams
  • Most upper-stack products are proprietary, not OSS
  • Platform sprawl can mean a steep onboarding curve
Website
Dataiku
dataiku.com
H2O.ai
h2o.ai

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.

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 H2O.ai if
  • ✅ Covers predictive ML and generative AI in one platform
  • ✅ Air-gapped and FedRAMP-ready deployment options
  • ✅ H2O-3 core is genuinely open source
  • ✅ Vertical agents for banking, telecom, and public sector
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