Skip to content
SlateIndex
DataikuThe Platform for AI Success
vs
Google Vertex AIGoogle Cloud's managed platform for training, deploying and operating ML models.
Comparison · MLOps Platforms · weekly run Nov 2

Dataiku vs Google Vertex AI

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

The short answer

Google Vertex AI is the stronger AI pick in MLOps Platforms: it has a visibility score of 33.1 versus 8.5 for Dataiku, and ranks ahead in 100% of the answers that name both.

Choose Dataiku if…

  • AI answers describe it more positively (48% vs 31% positive)
  • You need ISO 27001:2022 or ISO 27701:2019 or SOC 1 Type II or SOC 2 Type II or HIPAA or GxP or GDPR coverage
  • Bridges data scientists and business teams for collaboration
  • End-to-end governance and operationalization

Choose Google Vertex AI if…

  • You want the brand AI engines rank higher (33.1 vs 8.5)
  • You need ISO/IEC 27001 or ISO/IEC 27017 or ISO/IEC 27018 or ISO/IEC 27701 or ISO/IEC 42001 or SOC 1 or SOC 2 or SOC 3 or HIPAA-related attestations or PCI DSS or FedRAMP-related items coverage
  • unified ML platform across the lifecycle
  • strong Google Cloud integration

AI visibility side by side

Latest weekly run · Nov 2

Metric Dataiku Google Vertex AI
Visibility score8.5%33.1%
Change vs last weekNewNew
Rank in MLOps Platforms#12#5
Share of voice2.9%7.2%
Mentions this run2049
Positive in AI answers48%31%

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 2Dataiku 9%

Dataiku 0pp · Google Vertex AI 0pp over 0 weekly runs.

Engine by engine

Google Vertex AI leads on 3 of 3 engines

ChatGPT
12.2%
40.2%
AI Mode
9.3%
25.6%
Perplexity
3.9%
33.5%
DataikuGoogle Vertex AI

Head to head in AI answers

17 engine answers name both brands

0Dataiku ranked higher
17Google Vertex AI ranked higher

Features, pricing & fit

DimensionDataikuGoogle Vertex AI
DeploymentRuns on the clouds, data platforms and models a customer already hasManaged cloud service on Google Cloud
ComplianceISO 27001:2022, ISO 27701:2019, SOC 1 Type II, SOC 2 Type II, HIPAA, GxP, GDPRISO/IEC 27001, ISO/IEC 27017, ISO/IEC 27018, ISO/IEC 27701, ISO/IEC 42001, SOC 1, SOC 2, SOC 3, HIPAA-related attestations, PCI DSS, FedRAMP-related items
Founded20132021
HeadquartersNew York City, NYMountain View, California, United States
Employees1,001–5,000—
FundingSeries E · $600M raised—
Best forLarge 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

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

Google Vertex AI

  • unified ML platform across the lifecycle
  • strong Google Cloud integration
  • strong support for generative and foundation models
  • robust MLOps and agentic workflow support
  • $300 starter credits
  • less developer-centric for Python, Kubernetes and Git-based teams
  • usage-based costs depend on compute, storage and API usage

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

Cite as: SlateIndex, “Dataiku vs Google Vertex AI”, https://slateindex.ai/compare/dataiku-vs-google-vertex-ai, data of Nov 2, 2026. Licence: CC BY 4.0.