Skip to content
SlateIndex
DatabricksUnified data, analytics and AI platform on an open lakehouse
vs
DataikuThe Platform for AI Success
Comparison · MLOps Platforms · weekly run Nov 2

Databricks vs Dataiku

Which one do AI engines recommend, and how do they differ on price, fit and features?

The short answer

Databricks is the stronger AI pick in MLOps Platforms: it has a visibility score of 46.2 versus 8.5 for Dataiku, and ranks ahead in 90% of the answers that name both.

Choose Databricks if…

  • You want the brand AI engines rank higher (46.2 vs 8.5)
  • You need ISO 27001 or ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 3 coverage
  • You prefer a larger, established vendor (5,000+ employees)
  • Lakehouse architecture combining data warehousing with data lake flexibility

Choose Dataiku if…

  • AI answers describe it more positively (48% vs 35% positive)
  • You need ISO 27001:2022 or ISO 27701:2019 or SOC 1 Type II or HIPAA or GxP or GDPR coverage
  • Bridges data scientists and business teams for collaboration
  • End-to-end governance and operationalization

AI visibility side by side

Latest weekly run · Nov 2

Metric Databricks Dataiku
Visibility score46.2%8.5%
Change vs last weekNewNew
Rank in MLOps Platforms#2#12
Share of voice7.6%2.9%
Mentions this run5120
Positive in AI answers35%48%

The stronger value in each row is marked with a ✓.

Visibility score trend

Weekly runs over the last 60 days

0%25%50%75%100%Nov 2Databricks 46%

Databricks 0pp · Dataiku 0pp over 0 weekly runs.

Engine by engine

Databricks leads on 3 of 3 engines

ChatGPT
43.3%
12.2%
AI Mode
51.1%
9.3%
Perplexity
44.1%
3.9%
DatabricksDataiku

Head to head in AI answers

21 engine answers name both brands

19Databricks ranked higher
2Dataiku ranked higher

Features, pricing & fit

DimensionDatabricksDataiku
DeploymentAvailable across all major cloud providersRuns on the clouds, data platforms and models a customer already has
ComplianceISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3ISO 27001:2022, ISO 27701:2019, SOC 1 Type II, SOC 2 Type II, HIPAA, GxP, GDPR
SupportTechnical support on request, Technical documentation—
Founded20132013
HeadquartersSan Francisco, CANew York City, NY
Employees5,000+1,001–5,000
FundingRound at $60B valuation, including secondary saleSeries E · $600M raised
Best forData engineering, data science, analytics and AI teams at startups and global enterprisesLarge enterprises, including highly regulated ones, where business experts and IT need to build AI together under central governance

Pros and cons

Themes from the AI answers that mention each brand

Databricks

  • Lakehouse architecture combining data warehousing with data lake flexibility
  • Strong for machine learning, AI, and data engineering workloads
  • Top customer satisfaction ratings alongside Snowflake
  • Free trial and free Edition for learning
  • Discounts for annual prepaid commitments
  • Complex consumption-based pricing with no single fixed price
  • Best only when ML, Spark, or Python skills are central to the team

Dataiku

  • Bridges data scientists and business teams for collaboration
  • End-to-end governance and operationalization
  • Broad enterprise MLOps platform
  • Best for enterprise collaboration and governance
  • Steep platform fees that scale aggressively

Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run

Cite as: SlateIndex, “Databricks vs Dataiku”, https://slateindex.ai/compare/databricks-vs-dataiku, data of Nov 2, 2026. Licence: CC BY 4.0.