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Databricks SQL vs e6data

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. e6data: Lakehouse compute engine that runs SQL on Iceberg, Delta and Hudi in your own cloud account.

key differences

  • Databricks SQL is primarily a columnar / OLAP database; e6data is relational.
  • Databricks SQL is built for larger datasets (Multi-PB) than e6data (≤ 1 PB).
  • Transactions: Databricks SQL offers full ACID; e6data offers none.
  • Only Databricks SQL has transactions, vector search, geospatial, change data capture, materialized views.

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 e6data for

  • +Cutting lakehouse compute cost
  • +High-concurrency BI on Iceberg/Delta
  • +Offloading queries from Spark or warehouses

best at · Lakehouse, OLAP, Warehouse

Databricks SQLServerless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine.
e6dataLakehouse compute engine that runs SQL on Iceberg, Delta and Hudi in your own cloud account.
overview
Primary model
Columnar / OLAP
Relational
Also supports
Relational, Document, Vector, Spatial
Columnar / OLAP
Type
Managed service
Managed service
Status
Active
Active
Developer
Databricks
e6data
First release
2020
2023
Latest version
–
–
License
ProprietaryProprietary
ProprietaryProprietary
Free tier
✓
—
popularity
WhichDB Score
20.8
7.4
Rank
#147
#344
GitHub stars
–
–
Stack Overflow questions
543
–
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Full
None
Consistency
Strong
Strong
Schema
Flexible
Strict
Architecture
Serverless, Distributed, Shared storage
Distributed, 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, Trino/Spark-compatible dialects)
Client languages
Python, Java, JavaScript, Go, .NET
Python, Java
Best for
Lakehouse, Warehouse, OLAP
Lakehouse, OLAP, Warehouse
Add more to this comparisonNot sure either fits? Try smart match

Databricks SQL vs e6data: FAQ

What is the difference between Databricks SQL and e6data?

Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. e6data: Lakehouse compute engine that runs SQL on Iceberg, Delta and Hudi in your own cloud account. Databricks SQL is primarily a columnar / OLAP database; e6data is relational. Databricks SQL is built for larger datasets (Multi-PB) than e6data (≤ 1 PB). Transactions: Databricks SQL offers full ACID; e6data offers none.

When should I choose Databricks SQL over e6data?

Choose Databricks SQL for lakehouse SQL and BI on Delta Lake; consolidating a separate warehouse into Databricks; and dbt transformations on the lakehouse. Choose e6data for cutting lakehouse compute cost, high-concurrency BI on Iceberg/Delta and offloading queries from Spark or warehouses.

Is Databricks SQL or e6data more popular?

Databricks SQL ranks #147 on the WhichDB Score (20.8/100) and e6data ranks #344 (7.4/100). Popularity is not fit: check the requirements that matter for your project.

Are Databricks SQL and e6data open source?

No. Databricks SQL is proprietary, closed-source software. No. e6data is proprietary, closed-source software.