DataHub vs Stemma: Pricing and Ratings Compared (2026)
Entry prices and free plans as read on each vendor's pricing page, and user ratings as published on review sites, for DataHub and Stemma side by side. This page compares data; it is not a hands-on review.
On the data: On the data below, DataHub leads on a free plan. We do not name an overall winner for this pair.
Short on time? Here's the quick answer
Based on published vendor pricing and features and on public review data, here's who should pick what:
DataHub
Modern data catalog and metadata platform for AI and data context management.
Best for you if:
- • You want a free tier before you commit
Stemma
Automated data catalog for modern data teams.
Best for you if:
- • You want reduces manual effort in data cataloging
| At a Glance | DataHub | Stemma |
|---|---|---|
Starts at | Free plan | Not published |
Category | Data & Databases Analytics | Data & Databases Developer Tools |
Rating | 4.4/5 G2 4.4 8 reviews | n/a |
Free plan | Yes | No |
Watch out for | No public overage fee information for Cloud | n/a |
Choose DataHub or Stemma?
Choose DataHub if
- You want a free tier before you commit
- You want open-source core with a strong community
- You want scalable and extensible metadata graph
Choose Stemma if
- You want reduces manual effort in data cataloging
- You want improves data discoverability for data teams
In-Depth Analysis
DataHub
Modern data catalog and metadata platform for AI and data context management.
Watch out
No public overage fee information for Cloud
Strengths
- Pro: Open-source core with a strong community
- Pro: Scalable and extensible metadata graph
- Pro: Supports AI workflows and governance
- Pro: Offers a fully-managed SaaS option (DataHub Cloud)
- Pro: Proven by large enterprises like Netflix, Visa, and Slack
Weaknesses
- Con: No specific cons mentioned in the provided text.
Key features
Stemma
Automated data catalog for modern data teams.
Strengths
- Pro: Reduces manual effort in data cataloging
- Pro: Improves data discoverability for data teams
- Pro: Enhances trust in data through lineage and governance
- Pro: Accelerates data-driven decision making
Weaknesses
- Con: No explicit free tier mentioned
- Con: Pricing details not publicly available
Key features
Plans and prices: DataHub vs Stemma
| Tool | Plans and prices | Source |
|---|---|---|
| DataHub |
| datahubproject.io read Sep 30, 2026 |
| Stemma | No plan prices on file | stemma.ai |
Prices as read on each vendor's own pricing page on the date shown. Plans are listed per tool and are not matched against the other tool's plans: a plan name or price in one column says nothing about the same row in the other. Details on DataHub pricing and Stemma pricing.
Key Takeaways
DataHub
- Has a free plan
Stemma
- Choose if you want automated data catalog for modern data teams
What the data shows
On the data below, DataHub leads on a free plan. We do not name an overall winner for this pair.
- Only DataHub has a published user rating (4.4/5 from 8 reviews); Stemma has none we can show.
- Only DataHub has a free plan.
Criteria: user rating (only above 20 reviews on both sides, gap of 0.2 or more), entry price (only on the same billing basis), free plan. How we rate
Frequently Asked Questions
How do DataHub and Stemma compare in 2026?
On the data below, DataHub leads on a free plan. We do not name an overall winner for this pair. Only DataHub has a published user rating (4.4/5 from 8 reviews); Stemma has none we can show. Only DataHub has a free plan.
What are DataHub and Stemma used for?
DataHub: Modern data catalog and metadata platform for AI and data context management. Stemma: Automated data catalog for modern data teams.
What does DataHub cost vs Stemma?
DataHub has no public paid-plan price on file. Stemma has no public paid-plan price on file. Prices read on the vendors' pricing pages, latest check Sep 30, 2026.
What's the main difference between DataHub and Stemma?
DataHub's main strength: open-source core with a strong community. Stemma's main strength: reduces manual effort in data cataloging.