vs

1010data vs Databricks SQL

1010data: Hosted columnar analytics platform with a spreadsheet-style interface, owned by SymphonyAI since 2023. Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine.

key differences

  • Databricks SQL is built for larger datasets (Multi-PB) than 1010data (≤ 1 PB).
  • Transactions: 1010data offers limited ACID; Databricks SQL offers full.
  • Only Databricks SQL has transactions, vector search, geospatial, json, change data capture.
  • Databricks SQL has a serverless option; 1010data does not.

choose 1010data for

  • +Retail and CPG point-of-sale and loyalty analytics
  • +Retailer-to-supplier data sharing and collaboration
  • +Fixed-income and market data analysis
  • +Ad-hoc exploration of very large tables by non-engineers

best at · OLAP, Warehouse, Tick data

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

overview
Primary model
Columnar / OLAP
Columnar / OLAP
Also supports
Relational
Relational, Document, Vector, Spatial
Type
Managed service
Managed service
Status
Active
Active
Developer
1010data (SymphonyAI)
Databricks
First release
2000
2020
Latest version
–
–
License
ProprietaryProprietary
ProprietaryProprietary
Free tier
—
✓
popularity
WhichDB Score
0.0
20.8
Rank
#680
#147
GitHub stars
–
–
Stack Overflow questions
–
543
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Limited
Full
Consistency
Strong
Strong
Schema
Strict
Flexible
Architecture
Distributed
Serverless, Distributed, Shared storage
deployment
Self-hosted
—
—
Vendor-managed cloud
✓
✓
Serverless
—
✓
Embedded
—
—
Edge
—
—
Clouds
–
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
1010data Macro Language, SQL (via ODBC/JDBC drivers)
SQL (Databricks SQL / ANSI), Python
Client languages
Python, R, Java, .NET
Python, Java, JavaScript, Go, .NET
Best for
OLAP, Warehouse, Tick data
Lakehouse, Warehouse, OLAP

1010data vs Databricks SQL: FAQ

What is the difference between 1010data and Databricks SQL?

1010data: Hosted columnar analytics platform with a spreadsheet-style interface, owned by SymphonyAI since 2023. Databricks SQL: Serverless SQL warehouses on the Databricks lakehouse, powered by the Photon C++ engine. Databricks SQL is built for larger datasets (Multi-PB) than 1010data (≤ 1 PB). Transactions: 1010data offers limited ACID; Databricks SQL offers full. Only Databricks SQL has transactions, vector search, geospatial, json, change data capture.

When should I choose 1010data over Databricks SQL?

Choose 1010data for retail and CPG point-of-sale and loyalty analytics; retailer-to-supplier data sharing and collaboration; and fixed-income and market data analysis. Choose Databricks SQL for lakehouse SQL and BI on Delta Lake; consolidating a separate warehouse into Databricks; and dbt transformations on the lakehouse.

Is 1010data or Databricks SQL more popular?

Databricks SQL ranks #147 on the WhichDB Score (20.8/100) and 1010data ranks #680 (0.0/100). Popularity is not fit: check the requirements that matter for your project.

Are 1010data and Databricks SQL open source?

No. 1010data is proprietary, closed-source software. No. Databricks SQL is proprietary, closed-source software.