Dataiku vs Feast

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

The short answer

Dataiku is the stronger AI pick in MLOps Platforms: it has a visibility score of 8.5 versus 2 for Feast, and ranks ahead in 100% of the answers that name both.

Choose Dataiku if…

You want the brand AI engines rank higher (8.5 vs 2)
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 Feast if…

AI answers describe it more positively (50% vs 48% positive)
Connects with data lakes and warehouses for consistent data retrieval
Open-source, portable foundation option

AI visibility side by side

Latest weekly run · Nov 2

Metric	Dataiku	Feast
Visibility score	8.5%	2%
Change vs last week	New	New
Rank in MLOps Platforms	#12	#29
Share of voice	2.9%	0.6%
Mentions this run	20	4
Positive in AI answers	48%	50%

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

Dataiku leads on 3 of 3 engines

ChatGPT

12.2%

1.9%

AI Mode

9.3%

3.1%

Perplexity

3.9%

0.9%

DataikuFeast

Head to head in AI answers

2 engine answers name both brands

2Dataiku ranked higher

0Feast ranked higher

Prompt	Engine	Dataiku	Feast
What are the best MLOps Platforms tools in 2026?	ChatGPT	#10	#13
Official website of the top MLOps platform vendors	Perplexity	#7	#18

Features, pricing & fit

Dimension	Dataiku	Feast
Deployment	Runs on the clouds, data platforms and models a customer already has	Self-hosted; Kubernetes, and AWS Lambda (alpha)
Compliance	ISO 27001:2022, ISO 27701:2019, SOC 1 Type II, SOC 2 Type II, HIPAA, GxP, GDPR	—
Support	—	Community Slack, Documentation
Founded	2013	2018
Headquarters	New York City, NY	—
Employees	1,001–5,000	—
Funding	Series E · $600M raised	—
Best for	Large enterprises, including highly regulated ones, where business experts and IT need to build AI together under central governance	Machine learning and AI teams that need the same feature definitions for training and inference.