DatabricksUnified data, analytics and AI platform on an open lakehouse
vs
MakeAI automation you can visually build and orchestrate in real time.
Comparison · AI Agents · weekly run Nov 3
Databricks vs Make
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Make is the stronger AI pick in AI Agents: it has a visibility score of 17 versus 3 for Databricks, and ranks ahead in 0% of the answers that name both.
Choose Databricks if…
- You need ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 coverage
- You prefer a larger, established vendor (5,000+ employees)
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
Choose Make if…
- You want the brand AI engines rank higher (17 vs 3)
- AI answers describe it more positively (41% vs 35% positive)
- You need GDPR coverage
- Free tier with 1,000 credits per month
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Databricks | Make |
|---|---|---|
| Visibility score | 3% | 17% |
| Change vs last week | New | New |
| Rank in AI Agents | #30 | #9 |
| Share of voice | 0.9% | 3.6% |
| Mentions this run | 6 | 24 |
| Positive in AI answers | 35% | 41% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · Make 0pp over 0 weekly runs.
Engine by engine
Make leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
DatabricksMake
Head to head in AI answers
1 engine answers name both brands
1Databricks ranked higher
0Make ranked higher
| Prompt | Engine | Databricks | Make |
|---|---|---|---|
| What should an AI agent platform integrate with? | ChatGPT | #9 | #14 |
Features, pricing & fit
| Dimension | Databricks | Make |
|---|---|---|
| Deployment | Available across all major cloud providers | Cloud, hosted on Amazon AWS |
| Integrations | — | 3500+ |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | GDPR, SOC 2 Type II, SOC 3, ISO 27001 |
| Support | Technical support on request, Technical documentation | Help center, Community forum, 24/7 support on Enterprise plans, Dedicated support team on Enterprise plans |
| Founded | 2013 | 2012 |
| Headquarters | San Francisco, CA | Prague, Czech Republic |
| Employees | 5,000+ | 201–500 |
| Funding | Round at $60B valuation, including secondary sale | — |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | Teams and organizations deploying AI and automation across the business, from a single department to company-wide. |
Pros and cons
Themes from the AI answers that mention each brand
Databricks
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
- Free trial and free Edition for learning
- Discounts for annual prepaid commitments
- Complex consumption-based pricing with no single fixed price
- Best only when ML, Spark, or Python skills are central to the team
Make
- Free tier with 1,000 credits per month
- Transparent pricing with paid plans from $12/month
- Visual, no-code automation between existing apps
- Integrations with more than 3,000 apps
- Built-in AI agents for business workflows
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs Make”, https://slateindex.ai/compare/databricks-vs-make, data of Nov 3, 2026. Licence: CC BY 4.0.