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Apache DataFusion vs Apache Spark SQL

Apache DataFusion: Extensible Rust query engine library on Apache Arrow for building databases and data systems. Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing.

key differences

  • Apache DataFusion is primarily a columnar / OLAP database; Apache Spark SQL is relational.
  • Apache Spark SQL is built for larger datasets (Multi-PB) than Apache DataFusion (≤ 10 TB).
  • Horizontal scaling is addon in Apache DataFusion and native in Apache Spark SQL.
  • Transactions: Apache DataFusion offers none ACID; Apache Spark SQL offers limited.
  • Only Apache DataFusion has columnar storage, runs in webassembly.
  • Only Apache Spark SQL has json, durable persistence, compression, streaming ingest.
  • Apache DataFusion can run embedded in your application process.

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 apache-spark-sql for

  • +Lakehouse ETL and ELT
  • +Batch feature engineering for ML
  • +Streaming ingestion into Delta/Iceberg
  • +Large-scale data cleaning and joins

best at · Lakehouse, OLAP, Streaming

Apache DataFusionExtensible Rust query engine library on Apache Arrow for building databases and data systems.
Apache Spark SQLSpark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing.
overview
Primary model
Columnar / OLAP
Relational
Also supports
Relational
Columnar / OLAP, Document
Type
Embedded library
Database engine
Status
Active
Active
Developer
Apache Software Foundation
Apache Software Foundation
First release
2019
2014
Latest version
55.2.0 (Oct 7, 2026)
4.2.0 (Jul 14, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
31.6
50.3
Rank
#76
#26
GitHub stars
9.5K
44.3K
Stack Overflow questions
–
26.9K
scale & guarantees
Comfortable data size
Medium (≤ 10 TB)
Massive (Multi-PB)
Horizontal scaling
Addon
Native
Multi-region
None
None
ACID
None
Limited
Consistency
Strong
Strong
Schema
Strict
Flexible
Architecture
Embedded, In memory
Distributed, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
—
Serverless
—
—
Embedded
✓
—
Edge
—
—
Clouds
–
AWS, Google Cloud, Azure, Alibaba Cloud, Oracle 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, DataFrame API (Rust/Python), Substrait
Spark SQL (ANSI), Python (PySpark DataFrames), Scala, R
Client languages
Rust, Python
Python, Scala, Java, R, Go
Best for
OLAP, Embedded, Lakehouse
Lakehouse, OLAP, Streaming, Warehouse
Add more to this comparisonNot sure either fits? Try smart match

Apache DataFusion vs Apache Spark SQL: FAQ

What is the difference between Apache DataFusion and Apache Spark SQL?

Apache DataFusion: Extensible Rust query engine library on Apache Arrow for building databases and data systems. Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Apache DataFusion is primarily a columnar / OLAP database; Apache Spark SQL is relational. Apache Spark SQL is built for larger datasets (Multi-PB) than Apache DataFusion (≤ 10 TB). Horizontal scaling is addon in Apache DataFusion and native in Apache Spark SQL.

When should I choose Apache DataFusion over Apache Spark SQL?

Choose Apache DataFusion for building custom databases and query engines; embedded SQL in Rust services; and accelerating Spark via Comet. Choose Apache Spark SQL for lakehouse ETL and ELT; batch feature engineering for ML; and streaming ingestion into Delta/Iceberg.

Is Apache DataFusion or Apache Spark SQL more popular?

Apache Spark SQL ranks #26 on the WhichDB Score (50.3/100) and Apache DataFusion ranks #76 (31.6/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache DataFusion and Apache Spark SQL open source?

Yes. Apache DataFusion is open source. License: Apache License 2.0. Yes. Apache Spark SQL is open source. License: Apache License 2.0.