Databricks vs Google Gemini Enterprise
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Google Gemini Enterprise is the stronger AI pick in AI Agents: it has a visibility score of 19.4 versus 3 for Databricks, and ranks ahead in 50% of the answers that name both.
Choose Databricks if…
- You need SOC 2 Type II coverage
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
Choose Google Gemini Enterprise if…
- You want the brand AI engines rank higher (19.4 vs 3)
- AI answers describe it more positively (60% vs 35% positive)
- You need HIPAA or FedRAMP or SOC 2 or PCI DSS or BSI C5:2020 coverage
- Enterprise-grade infrastructure for building agents
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Databricks | Google Gemini Enterprise |
|---|---|---|
| Visibility score | 3% | 19.4% |
| Change vs last week | New | New |
| Rank in AI Agents | #30 | #6 |
| Share of voice | 0.9% | 4.3% |
| Mentions this run | 6 | 28 |
| Positive in AI answers | 35% | 60% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · Google Gemini Enterprise 0pp over 0 weekly runs.
Engine by engine
Google Gemini Enterprise leads on 3 of 3 engines
Head to head in AI answers
6 engine answers name both brands
| Prompt | Engine | Databricks | Google Gemini Enterprise |
|---|---|---|---|
| How do companies build and deploy AI agents that automate work without a dedicated tool? | ChatGPT | #10 | #6 |
| What is the difference between an AI agent platform and MLOps Platforms? | ChatGPT | #8 | #2 |
| What should an AI agent platform integrate with? | ChatGPT | #9 | #18 |
| Best AI agent platform for enterprise | AI Mode | #4 | #9 |
| Which AI Agents vendors do analysts recommend? | ChatGPT | #8 | #2 |
| Which AI Agents vendors do analysts recommend? | Perplexity | #2 | #5 |
Features, pricing & fit
| Dimension | Databricks | Google Gemini Enterprise |
|---|---|---|
| Deployment | Available across all major cloud providers | — |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | HIPAA, FedRAMP, ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2, SOC 3, PCI DSS, BSI C5:2020 |
| Support | Technical support on request, Technical documentation | — |
| Founded | 2013 | 2025 |
| Headquarters | San Francisco, CA | — |
| Employees | 5,000+ | — |
| Funding | Round at $60B valuation, including secondary sale | — |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | — |
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
Google Gemini Enterprise
- Enterprise-grade infrastructure for building agents
- Free trial credits for new customers
- Rated Exemplary by ISG
- Native connectors to databases and cloud storage
- End-to-end agent development and deployment
- High base and per-action costs
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs Google Gemini Enterprise”, https://slateindex.ai/compare/databricks-vs-google-gemini-enterprise, data of Nov 3, 2026. Licence: CC BY 4.0.