Databricks vs SuperAnnotate
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Databricks is the stronger AI pick in MLOps Platforms: it has a visibility score of 46.2 versus 2.1 for SuperAnnotate, and ranks ahead in 100% of the answers that name both.
Choose Databricks if…
- You want the brand AI engines rank higher (46.2 vs 2.1)
- You need ISO 27001 or ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 3 coverage
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
Choose SuperAnnotate if…
- You need ISO 27001:2022 coverage
- high rating from many reviews
- well suited to data labeling and annotation workflows
AI visibility side by side
Latest weekly run · Nov 2
| Metric | Databricks | SuperAnnotate |
|---|---|---|
| Visibility score | 46.2% | 2.1% |
| Change vs last week | New | New |
| Rank in MLOps Platforms | #2 | #28 |
| Share of voice | 7.6% | 0.3% |
| Mentions this run | 51 | 2 |
| Positive in AI answers | 35% | — |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · SuperAnnotate 0pp over 0 weekly runs.
Engine by engine
Databricks leads on 3 of 3 engines
Head to head in AI answers
2 engine answers name both brands
| Prompt | Engine | Databricks | SuperAnnotate |
|---|---|---|---|
| Which MLOps platform has the best reviews? | ChatGPT | #1 | #2 |
| Which MLOps platform has the best reviews? | Perplexity | #1 | #2 |
Features, pricing & fit
| Dimension | Databricks | SuperAnnotate |
|---|---|---|
| Pricing model | — | Flat tiers |
| Entry price | — | Contact sales |
| Free plan | — | No |
| Deployment | Available across all major cloud providers | — |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | SOC 2 Type II, ISO 27001:2022 |
| Support | Technical support on request, Technical documentation | Dedicated Slack channel (Pro and Enterprise plans), Dedicated customer success manager (Pro and Enterprise plans), Dedicated solutions engineer (Enterprise plan), AI DataOps consulting (Enterprise plan) |
| Founded | 2013 | 2018 |
| Headquarters | San Francisco, CA | Silicon Valley, California |
| Employees | 5,000+ | — |
| Funding | Round at $60B valuation, including secondary sale | Series B extension (Dell Technologies Capital) · $50M raised |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | Frontier AI teams and well-established enterprises running recurring, high-volume AI data projects. |
Plans side by side
Databricks
Pricing not available.
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
SuperAnnotate
- high rating from many reviews
- well suited to data labeling and annotation workflows
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs SuperAnnotate”, https://slateindex.ai/compare/databricks-vs-superannotate, data of Nov 2, 2026. Licence: CC BY 4.0.