AI Data
Azure Machine Learning vs Holistics
Two ai data tools, what each is better at, what each costs, and the one we would pick.
We rate it higher

Azure Machine Learning
Cloud service for the end-to-end machine learning lifecycle
Pros
- ✓ Listed by Microsoft as an Azure service for the end-to-end machine learning lifecycle.
- ✓ Sits inside the broader Azure AI portfolio alongside Microsoft Foundry and Foundry Tools.
- ✓ Billed through Azure's consumption model, so cost scales with resources used.
Cons
- ✗ The pages reviewed do not list a standalone price or plan tiers for Azure Machine Learning.
- ✗ There is no permanent free tier for the service; the free offer is a 30-day Azure account trial.
We rate it higher

Holistics
From $800/mo
Self-service BI and AI analytics on a code-defined semantic layer
Pros
- ✓ Metrics, models and dashboards are defined as code in AML with Git version control and pull-request review.
- ✓ The same semantic layer feeds dashboards, AI answers and embedded analytics, so numbers stay consistent across surfaces.
- ✓ The semantic layer can be queried from external tools such as Claude, ChatGPT and Cursor over MCP and APIs.
Cons
- ✗ No free plan is listed; the cheapest paid plan is $800/month on yearly billing.
- ✗ Every plan includes only the first 10 users, and additional users are charged as add-ons.
| Azure Machine Learning | Holistics | |
|---|---|---|
| From | Contact | $800/mo |
| Free Tier | No | No |
| Our Rating | Not rated | Not rated |
| Pricing | paid | paid |
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Summary
We have not used both of these yet, so there is no score to pick a winner with. What they cost, who they suit and what each one does is in the table above.
Azure Machine Learning Full Review →Holistics Full Review →Azure Machine Learning Alternatives →Holistics Alternatives →
Some links here earn us a commission. We earn it whether we praised the tool or not, which is why the verdict does not move for it.