Head-to-head · Low-Code Machine Learning Platforms Software
Databricks Mosaic AI vs KNIME Analytics Platform
Databricks Mosaic AI leads on 0 checks, KNIME Analytics Platform on 1, and 0 are even. Who comes out ahead on the 1 yes/no, price and count check where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreDatabricks Mosaic AI · 7.2/10
- Free planonly KNIME Analytics Platform
Databricks Mosaic AI scores higher on our rubric for low-code machine learning platforms software: 7.2 against 6.5 out of 10; our editors rank them #4 and #8.
KNIME Analytics Platform offers free plan; Databricks Mosaic AI doesn't publish it.
Databricks Mosaic AI is the better fit for data teams already building on Databricks. KNIME Analytics Platform is the better fit for budget-conscious teams building visual data workflows.
- Databricks Mosaic AI fits best
Data teams already building on Databricks
- KNIME Analytics Platform fits best
Budget-conscious teams building visual data workflows
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Side by side
| Feature | Databricks Mosaic AI 7.2/10 Visit ↗ | KNIME Analytics Platform 6.5/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 7.2 | 6.5 |
| Ranking | #4 in Low-Code Machine Learning Platforms Software | #8 in Low-Code Machine Learning Platforms Software |
| Best for | Data teams already building on Databricks | Budget-conscious teams building visual data workflows |
| Pricing model | Paid | Free |
| Starting price | Not published | Not published |
| Free plan | Not published | ✓ (best) |
| Free trial | — | — |
| Deployment | Cloud | Desktop, Self-hosted, Cloud |
| Platforms | Web | Windows, macOS, Linux |
| Support | Docs | Community, Docs |
| Built for | Mid-market, Enterprise | Solo, Small business, Mid-market, Enterprise |
| Features Databricks Mosaic AI 0/2 · KNIME Analytics Platform 0/2 | ||
| Automated ML | Not published | Not published |
| Visual workflows | Not published | Not published |
| Specs | ||
| Deployment targets | Not published | Not published |
| Supported model types | Not published | Not published |
| Data source connectors | Not published | Not published |
| Access platforms | Not published | Not published |
| Our review | ||
| Pros |
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| Cons |
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| Our verdict | Databricks Mosaic AI brings together tools for developing, deploying, monitoring, and governing machine-learning and generative-AI applications. It is aimed at technical teams and organizations building production AI systems in enterprise… Read the review → |
KNIME Analytics Platform is a free, open-source application for building visual workflows across data access, preparation, analysis, modeling, and visualization. It is intended for data analysts, data scientists, business users, and teams… Read the review → |
Strengths and trade-offs
Databricks Mosaic AI — where it wins
- Tracks experiments and versions models through MLflow and Unity Catalog.
- Combines orchestration, managed compute, and batch or real-time inference.
- Supports serving and monitoring models through REST endpoints.
Where it doesn't
- Cloud deployment only.
- Usage-based costs vary by cloud provider, region, and selected services.
- Documentation is the listed support channel.
KNIME Analytics Platform — where it wins
- Free, open-source platform with desktop, self-hosted, and cloud deployment
- 300+ connectors plus Python, R, JavaScript, and major data platforms
- Forecasting, reusable components, visualizations, and REST API deployment
Where it doesn't
- No automated ML capability
- Real-time REST deployment requires KNIME Hub or Server
- Support is centered on community resources and documentation
- Databricks Mosaic AI7.2/10 · 14-day trial
A cloud-focused ML lifecycle platform for teams building on Databricks.
Visit DatabricksFull verdict → - KNIME Analytics Platform6.5/10 · Free plan
A free, visual ML platform with broad connectors and scripting, but no automated ML.
Visit KNIMEFull verdict →
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All Low-Code machine learning platforms software comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
Last updated · How we research and update







