vs

Apache DataFusion vs DuckDB

Apache DataFusion: Extensible Rust query engine library on Apache Arrow for building databases and data systems. DuckDB: In-process columnar SQL database: the SQLite of analytics, running inside your app or notebook.

key differences

  • Horizontal scaling is addon in Apache DataFusion and none in DuckDB.
  • Transactions: Apache DataFusion offers none ACID; DuckDB offers full.
  • Only DuckDB has transactions, secondary indexes, full-text search, vector search, geospatial.

choose apache-datafusion for

  • +Building custom databases and query engines
  • +Embedded SQL in Rust services
  • +Accelerating Spark via Comet
  • +Query layer for time-series or log stores

best at · OLAP, Embedded, Lakehouse

choose duckdb for

  • +Local data analysis in notebooks
  • +ETL and data-engineering pipelines on files
  • +Embedded analytics inside applications
  • +Querying data lakes on S3 without a cluster

best at · OLAP, Embedded, Lakehouse

overview
Primary model
Columnar / OLAP
Columnar / OLAP
Also supports
Relational
Relational, Document, Spatial, Vector
Type
Embedded library
Database engine
Status
Active
Active
Developer
Apache Software Foundation
DuckDB Foundation / DuckDB Labs
First release
2019
2019
Latest version
55.2.0 (Oct 7, 2026)
2.0.0 (Oct 21, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)MIT License
Free tier
✓
✓
popularity
WhichDB Score
31.6
63.7
Rank
#76
#13
GitHub stars
9.5K
42.6K
Stack Overflow questions
–
501
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Medium (≤ 10 TB)
Horizontal scaling
Addon
None
Multi-region
None
None
ACID
None
Full
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Embedded, In memory
Embedded, Single node, In memory
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
—
Serverless
—
—
Embedded
✓
✓
Edge
—
—
Clouds
–
–
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, DataFrame API (Rust/Python), Substrait
SQL (PostgreSQL-like dialect)
Client languages
Rust, Python
Python, R, Java, JavaScript, Go, Rust, C, Swift
Best for
OLAP, Embedded, Lakehouse
OLAP, Embedded, Lakehouse, Warehouse

Apache DataFusion vs DuckDB: FAQ

What is the difference between Apache DataFusion and DuckDB?

Apache DataFusion: Extensible Rust query engine library on Apache Arrow for building databases and data systems. DuckDB: In-process columnar SQL database: the SQLite of analytics, running inside your app or notebook. Horizontal scaling is addon in Apache DataFusion and none in DuckDB. Transactions: Apache DataFusion offers none ACID; DuckDB offers full. Only DuckDB has transactions, secondary indexes, full-text search, vector search, geospatial.

When should I choose Apache DataFusion over DuckDB?

Choose Apache DataFusion for building custom databases and query engines; embedded SQL in Rust services; and accelerating Spark via Comet. Choose DuckDB for local data analysis in notebooks; ETL and data-engineering pipelines on files; and embedded analytics inside applications.

Is Apache DataFusion or DuckDB more popular?

DuckDB ranks #13 on the WhichDB Score (63.7/100) and Apache DataFusion ranks #76 (31.6/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache DataFusion and DuckDB open source?

Yes. Apache DataFusion is open source. License: Apache License 2.0. Yes. DuckDB is open source. License: MIT License.