ClouderaThe hybrid data and AI platform that brings AI to data anywhere
vs
ExasolThe sovereign analytics database for high-concurrency AI and analytics workloads
Comparison · Data Warehouse · weekly run Nov 3
Cloudera vs Exasol
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Exasol is the stronger AI pick in Data Warehouse: it has a visibility score of 2 versus 1 for Cloudera, and ranks ahead in 0% of the answers that name both.
Choose Cloudera if…
- You prefer a larger, established vendor (1,001–5,000 employees)
Choose Exasol if…
- You want the brand AI engines rank higher (2 vs 1)
- You need ISO/IEC 27001:2022 coverage
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Cloudera | Exasol |
|---|---|---|
| Visibility score | 1% | 2% |
| Change vs last week | New | New |
| Rank in Data Warehouse | #25 | #22 |
| Share of voice | 0.5% | 0.5% |
| Mentions this run | 3 | 3 |
| Positive in AI answers | 0% | 0% |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Cloudera 0pp · Exasol 0pp over 0 weekly runs.
Engine by engine
Exasol leads on 3 of 3 engines
ChatGPT
AI Mode
Perplexity
ClouderaExasol
Head to head in AI answers
1 engine answers name both brands
1Cloudera ranked higher
0Exasol ranked higher
| Prompt | Engine | Cloudera | Exasol |
|---|---|---|---|
| Official website of the top data warehouse vendors | ChatGPT | #11 | #13 |
Features, pricing & fit
| Dimension | Cloudera | Exasol |
|---|---|---|
| Deployment | Public clouds, sovereign clouds, private data centers, air-gapped networks and the edge | On-premises, hybrid and cloud |
| Compliance | — | ISO/IEC 27001:2022 |
| Support | Support Portal, Cloudera Professional Services | — |
| Founded | — | 2000 |
| Headquarters | Santa Clara, California, US | Nürnberg, Germany |
| Employees | 1,001–5,000 | 201–500 |
| Funding | Take-private by KKR · $1041M raised | Series A · $86M raised |
| Best for | Large enterprises and public sector organizations that need AI and analytics on data spread across clouds, data centers and the edge. | Enterprises and data teams, including CTOs, heads of data and analytics, data engineers and data scientists, that need fast high-concurrency analytics and AI workloads on-premises, hybrid or in the cloud |
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Cloudera vs Exasol”, https://slateindex.ai/compare/cloudera-vs-exasol, data of Nov 3, 2026. Licence: CC BY 4.0.