vs

Databricks SQL vs Starburst

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Starburst: Commercial Trino platform: self-managed Starburst Enterprise and the Starburst Galaxy SaaS.

key differences

  • Databricks SQL is primarily a columnar / OLAP database; Starburst is relational.
  • Transactions: Databricks SQL offers full ACID; Starburst offers limited.
  • Only Databricks SQL has transactions, vector search, change data capture, columnar storage, durable persistence.

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 starburst for

  • +Enterprise lakehouse on Iceberg
  • +Data mesh and data products
  • +Federated queries across on-prem and cloud
  • +Warehouse offload from Teradata or Netezza

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
Starburst Data
First release
2020
2017
Latest version
–
483-e (Oct 16, 2026)
License
ProprietaryProprietary
ProprietaryProprietary (on an Apache-2.0 Trino core)
Free tier
✓
—
popularity
WhichDB Score
20.8
0.0
Rank
#147
#820
GitHub stars
–
–
Stack Overflow questions
543
–
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Full
Limited
Consistency
Strong
Strong
Schema
Flexible
Strict
Architecture
Serverless, Distributed, Shared storage
Distributed, Client server, Serverless
deployment
Self-hosted
—
✓
Vendor-managed cloud
✓
✓
Serverless
✓
✓
Embedded
—
—
Edge
—
—
Clouds
AWS, Azure, Google Cloud
AWS, Azure, Google Cloud
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 (ANSI)
Client languages
Python, Java, JavaScript, Go, .NET
Java, Python, Go, JavaScript
Best for
Lakehouse, Warehouse, OLAP
Lakehouse, OLAP, Warehouse

Databricks SQL vs Starburst: FAQ

What is the difference between Databricks SQL and Starburst?

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Starburst: Commercial Trino platform: self-managed Starburst Enterprise and the Starburst Galaxy SaaS. Databricks SQL is primarily a columnar / OLAP database; Starburst is relational. Transactions: Databricks SQL offers full ACID; Starburst offers limited. Only Databricks SQL has transactions, vector search, change data capture, columnar storage, durable persistence.

When should I choose Databricks SQL over Starburst?

Choose Databricks SQL for lakehouse SQL and BI on Delta Lake; consolidating a separate warehouse into Databricks; and dbt transformations on the lakehouse. Choose Starburst for enterprise lakehouse on Iceberg; data mesh and data products; and federated queries across on-prem and cloud.

Is Databricks SQL or Starburst more popular?

Databricks SQL ranks #147 on the WhichDB Score (20.8/100) and Starburst ranks #820 (0.0/100). Popularity is not fit: check the requirements that matter for your project.

Are Databricks SQL and Starburst open source?

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