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Apache Paimon vs Apache Spark SQL

Apache Paimon: Streaming lakehouse table format with LSM-based upserts and changelogs, born in Apache Flink. Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing.

key differences

  • Apache Paimon is primarily a columnar / OLAP database; Apache Spark SQL is relational.
  • Transactions: Apache Paimon offers full ACID; Apache Spark SQL offers limited.
  • Only Apache Paimon has transactions, change data capture, columnar storage, time travel, branching.
  • Only Apache Spark SQL has joins, json, in-memory.
  • Apache Paimon can run embedded in your application process.

choose apache-paimon for

  • +Streaming CDC from databases into the lake
  • +Real-time lakehouse with Flink
  • +Incremental ETL with changelogs
  • +Partial-update wide tables

best at · Lakehouse, Streaming, Real-time analytics

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 PaimonStreaming lakehouse table format with LSM-based upserts and changelogs, born in Apache Flink.
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
2023
2014
Latest version
2.1.0 (Oct 12, 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
14.2
50.3
Rank
#237
#26
GitHub stars
3.4K
44.3K
Stack Overflow questions
–
26.9K
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
Strict
Flexible
Architecture
Distributed, Shared storage
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 (via Flink, Spark, Trino, StarRocks, Doris)
Spark SQL (ANSI), Python (PySpark DataFrames), Scala, R
Client languages
Java, Python
Python, Scala, Java, R, Go
Best for
Lakehouse, Streaming, Real-time analytics
Lakehouse, OLAP, Streaming, Warehouse
Add more to this comparisonNot sure either fits? Try smart match

Apache Paimon vs Apache Spark SQL: FAQ

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

Apache Paimon: Streaming lakehouse table format with LSM-based upserts and changelogs, born in Apache Flink. Apache Spark SQL: Spark's SQL and DataFrame engine for large-scale batch, streaming and lakehouse processing. Apache Paimon is primarily a columnar / OLAP database; Apache Spark SQL is relational. Transactions: Apache Paimon offers full ACID; Apache Spark SQL offers limited. Only Apache Paimon has transactions, change data capture, columnar storage, time travel, branching.

When should I choose Apache Paimon over Apache Spark SQL?

Choose Apache Paimon for streaming CDC from databases into the lake, real-time lakehouse with Flink and incremental ETL with changelogs. Choose Apache Spark SQL for lakehouse ETL and ELT; batch feature engineering for ML; and streaming ingestion into Delta/Iceberg.

Is Apache Paimon or Apache Spark SQL more popular?

Apache Spark SQL ranks #26 on the WhichDB Score (50.3/100) and Apache Paimon ranks #237 (14.2/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache Paimon and Apache Spark SQL open source?

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