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Apache Paimon vs StarRocks

Apache Paimon: Streaming lakehouse table format with LSM-based upserts and changelogs, born in Apache Flink. StarRocks: MPP OLAP database with a fast vectorized engine, real-time upserts and native lakehouse queries.

key differences

  • Apache Paimon is built for larger datasets (Multi-PB) than StarRocks (≤ 1 PB).
  • Transactions: Apache Paimon offers full ACID; StarRocks offers limited.
  • Only Apache Paimon has transactions, change data capture, time travel, branching.
  • Only StarRocks has joins, secondary indexes, full-text search, vector search, json.
  • 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 starrocks for

  • +Real-time dashboards with joins
  • +Lakehouse query acceleration over Iceberg
  • +Customer-facing analytics
  • +Replacing pre-aggregated cubes

best at · Real-time analytics, OLAP, Lakehouse

overview
Primary model
Columnar / OLAP
Columnar / OLAP
Also supports
Relational
Relational, Document, Vector
Type
Embedded library
Database engine
Status
Active
Active
Developer
Apache Software Foundation
StarRocks (Linux Foundation; CelerData)
First release
2023
2020
Latest version
2.1.0 (Oct 12, 2026)
4.1.3 (Sep 17, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
14.2
15.6
Rank
#237
#210
GitHub stars
3.4K
12.2K
Stack Overflow questions
–
11
scale & guarantees
Comfortable data size
Massive (Multi-PB)
Large (≤ 1 PB)
Horizontal scaling
Native
Native
Multi-region
None
None
ACID
Full
Limited
Consistency
Strong
Strong
Schema
Strict
Strict
Architecture
Distributed, Shared storage
Distributed, Shared storage
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 (via Flink, Spark, Trino, StarRocks, Doris)
SQL (MySQL dialect)
Client languages
Java, Python
Java, Python, Go, JavaScript, C++
Best for
Lakehouse, Streaming, Real-time analytics
Real-time analytics, OLAP, Lakehouse, Warehouse

Apache Paimon vs StarRocks: FAQ

What is the difference between Apache Paimon and StarRocks?

Apache Paimon: Streaming lakehouse table format with LSM-based upserts and changelogs, born in Apache Flink. StarRocks: MPP OLAP database with a fast vectorized engine, real-time upserts and native lakehouse queries. Apache Paimon is built for larger datasets (Multi-PB) than StarRocks (≤ 1 PB). Transactions: Apache Paimon offers full ACID; StarRocks offers limited. Only Apache Paimon has transactions, change data capture, time travel, branching.

When should I choose Apache Paimon over StarRocks?

Choose Apache Paimon for streaming CDC from databases into the lake, real-time lakehouse with Flink and incremental ETL with changelogs. Choose StarRocks for real-time dashboards with joins, lakehouse query acceleration over Iceberg and customer-facing analytics.

Is Apache Paimon or StarRocks more popular?

StarRocks ranks #210 on the WhichDB Score (15.6/100) and Apache Paimon ranks #237 (14.2/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache Paimon and StarRocks open source?

Yes. Apache Paimon is open source. License: Apache License 2.0. Yes. StarRocks is open source. License: Apache License 2.0.