shouldiuse.io

Comparison

Databricks vs Dremio

Databricks and Dremio both land on Depends.

Dremio

Depends
Confidence: Medium

Buy if you are a mid-size or large org with lake-scale data on S3 and dedicated data engineers.

Add this comparison to your site

Put the Databricks vs Dremio badge on your site.

Visitors see the independent comparison.

The link points here, and search engines follow it.

This is the badge visitors see on your site.

Paste one snippet. Keep the link as it is. A nofollow tag stops search engines from following it.

Databricks versus Dremio
CompareDatabricksDremio
VerdictDependsDepends
Best forEnterprise data teamsEnterprises with data lakes on S3
Who it's not forSmall teams wanting simple analyticsSmall teams that just need a dashboard
PrivacyActive security program (bug bounty, trust center) but several CVEs in 2024-2026, including a critical Azure SSRF flaw.10One known auth-bypass CVE (2025); otherwise strong posture . CVE Numbering Authority, certifications, build scanning.
Support qualityNo support-quality evidence foundNo usable evidence
Public sentimentReviewers rate Databricks highly for capability and UX, but cost predictability is the loudest complaint.¹Users praise the SQL simplicity and lakehouse speed but report heavy setup and a smaller community than Databricks or Snowflake.15
Biggest gotchaDBU pricing is opaque; buyers report unpredictable bills and overruns¹Self-hosted OSS ships dependency CVEs; patching is on your team.

Pick Databricks when

  • Enterprise data teams
  • Large-scale ETL and ML
  • Unified lakehouse with governance
  • AI-focused orgs on cloud data

When Databricks is not a fit

  • Small teams wanting simple analytics
  • Startups without dedicated data engineers
  • Price-sensitive buyers needing predictable bills
  • Dashboard-only BI needs

Pick Dremio when

  • Enterprises with data lakes on S3
  • SQL-first BI and analytics teams
  • Orgs building AI on lakehouse data

When Dremio is not a fit

  • Small teams that just need a dashboard
  • Anyone without dedicated data engineers
  • Startups wanting predictable flat pricing
  • Spark/ML-heavy shops better served by Databricks

Sources

  1. review
  2. review
  3. review
  4. review
  5. news
  6. news
  7. news
  8. news
  9. news
  10. security
  11. security
  12. security
  13. official
  14. official
  15. review
  16. review