vs

Databricks SQL vs Dremio

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Dremio: Iceberg-native lakehouse query engine with reflections for acceleration, owned by SAP since 2026.

key differences

  • Databricks SQL is primarily a columnar / OLAP database; Dremio is relational.
  • Databricks SQL is built for larger datasets (Multi-PB) than Dremio (≤ 1 PB).
  • Transactions: Databricks SQL offers full ACID; Dremio offers limited.
  • Only Databricks SQL has transactions, vector search, geospatial, change data capture, columnar storage.
  • Databricks SQL has a serverless option; Dremio does not.

choose databricks-sql for

  • +Lakehouse SQL and BI on Delta Lake
  • +Consolidating a separate warehouse into Databricks
  • +dbt transformations on the lakehouse
  • +Serving features and aggregates for ML

best at · Lakehouse, Warehouse, OLAP

choose dremio for

  • +Iceberg lakehouse BI acceleration
  • +Semantic layer over a data lake
  • +SAP-centric data platforms
  • +Warehouse offload

best at · Lakehouse, OLAP, Warehouse

overview
Primary model
Columnar / OLAP
Relational
Also supports
Relational, Document, Vector, Spatial
Columnar / OLAP
Type
Managed service
Database engine
Status
Active
Active
Developer
Databricks
Dremio (SAP)
First release
2020
2017
Latest version
–
–
License
ProprietaryProprietary
ProprietaryProprietary (legacy Community Edition under Apache-2.0)
Free tier
✓
—
popularity
WhichDB Score
20.8
12.7
Rank
#147
#262
GitHub stars
–
1.5K
Stack Overflow questions
543
74
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Full
Limited
Consistency
Strong
Strong
Schema
Flexible
Strict
Architecture
Serverless, Distributed, Shared storage
Distributed, Shared storage, Client server
deployment
Self-hosted
—
✓
Vendor-managed cloud
✓
✓
Serverless
✓
—
Embedded
—
—
Edge
—
—
Clouds
AWS, Azure, Google Cloud
AWS, Azure
capabilities
Transactions
✓
—
Joins
✓
✓
Secondary indexes
—
—
Full-text search
—
—
Vector search
✓
—
Geospatial
✓
—
JSON
✓
✓
Change data capture
✓
—
Triggers
—
—
Stored procedures
—
—
Materialized views
✓
✓
TTL / expiry
—
—
Pub/Sub
—
—
Columnar storage
✓
—
In-memory
—
—
Durable persistence
✓
✓
Compression
✓
✓
Encryption at rest
✓
✓
Role-based access
✓
✓
Time travel
✓
✓
Branching
—
—
Online schema changes
✓
—
Streaming ingest
✓
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
SQL (Databricks SQL / ANSI), Python
SQL
Client languages
Python, Java, JavaScript, Go, .NET
Python, Java, Go, JavaScript
Best for
Lakehouse, Warehouse, OLAP
Lakehouse, OLAP, Warehouse

Databricks SQL vs Dremio: FAQ

What is the difference between Databricks SQL and Dremio?

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Dremio: Iceberg-native lakehouse query engine with reflections for acceleration, owned by SAP since 2026. Databricks SQL is primarily a columnar / OLAP database; Dremio is relational. Databricks SQL is built for larger datasets (Multi-PB) than Dremio (≤ 1 PB). Transactions: Databricks SQL offers full ACID; Dremio offers limited.

When should I choose Databricks SQL over Dremio?

Choose Databricks SQL for lakehouse SQL and BI on Delta Lake; consolidating a separate warehouse into Databricks; and dbt transformations on the lakehouse. Choose Dremio for iceberg lakehouse BI acceleration, semantic layer over a data lake and SAP-centric data platforms.

Is Databricks SQL or Dremio more popular?

Databricks SQL ranks #147 on the WhichDB Score (20.8/100) and Dremio ranks #262 (12.7/100). Popularity is not fit: check the requirements that matter for your project.

Are Databricks SQL and Dremio open source?

No. Databricks SQL is proprietary, closed-source software. No. Dremio is proprietary, closed-source software.