Feast vs GitHub

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

The short answer

GitHub is the stronger AI pick in MLOps Platforms: it has a visibility score of 9 versus 2 for Feast, and ranks ahead in 50% of the answers that name both.

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

Choose GitHub if…

You want the brand AI engines rank higher (9 vs 2)
You need a self-hosted or on-premises option
You need SOC 1 Type 2 or SOC 2 Type 2 or ISO/IEC 27001 or CSA STAR Level 2 or PCI DSS or FedRAMP Tailored ATO coverage
Most widely adopted CI/CD tool today

AI visibility side by side

Latest weekly run · Nov 2

Metric	Feast	GitHub
Visibility score	2%	9%
Change vs last week	New	New
Rank in MLOps Platforms	#29	#11
Share of voice	0.6%	2%
Mentions this run	4	14
Positive in AI answers	50%	48%

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

Visibility score trend

Weekly runs over the last 60 days

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

Engine by engine

GitHub leads on 3 of 3 engines

ChatGPT

1.9%

11.5%

AI Mode

3.1%

5.6%

Perplexity

0.9%

10%

FeastGitHub

Head to head in AI answers

2 engine answers name both brands

1Feast ranked higher

1GitHub ranked higher

Prompt	Engine	Feast	GitHub
What should an MLOps platform integrate with?	ChatGPT	#8	#4
What should an MLOps platform integrate with?	AI Mode	#2	#4

Features, pricing & fit

Dimension	Feast	GitHub
Pricing model	—	Per seat
Entry price	—	Free; paid from $4 per seat / mo
Free plan	—	Yes
Deployment	Self-hosted; Kubernetes, and AWS Lambda (alpha)	Cloud service (GitHub.com and GitHub Enterprise Cloud) and self-hosted GitHub Enterprise Server
Compliance	—	SOC 1 Type 2, SOC 2 Type 2, ISO/IEC 27001, CSA STAR Level 2, PCI DSS, FedRAMP Tailored ATO
Support	Community Slack, Documentation	Community support (Free plan), Web-based support (Team plan), Premium support with 24/7 web and phone support and a 30-minute SLA on urgent tickets (Enterprise)
Founded	2018	2008
Headquarters	—	San Francisco, California
Employees	—	501–1,000
Funding	—	Round led by Sequoia Capital · $350M raised
Best for	Machine learning and AI teams that need the same feature definitions for training and inference.	Development teams, from individuals to enterprises, that build, review, and ship software on one platform.