vs

Apache Kudu vs ClickHouse

Apache Kudu: Columnar storage engine for fast analytics on fast-changing data, paired with Impala or Spark. ClickHouse: Open-source columnar OLAP database known for very fast aggregations over billions of rows.

key differences

  • ClickHouse is built for larger datasets (Multi-PB) than Apache Kudu (≤ 1 PB).
  • Only ClickHouse has joins, secondary indexes, full-text search, vector search, geospatial.
  • ClickHouse has a serverless option; Apache Kudu does not.

choose apache-kudu for

  • +Mutable fact tables in Cloudera
  • +Near-real-time analytics with Impala
  • +Time-series with updates

best at · Real-time analytics, OLAP, Time-series

choose clickhouse for

  • +Product and web analytics
  • +Log and observability backends
  • +Real-time dashboards over event streams
  • +Time-series and IoT metrics at scale

best at · Real-time analytics, OLAP, Observability

overview
Primary model
Columnar / OLAP
Columnar / OLAP
Also supports
Relational
Relational, Document, Vector, Time-Series
Type
Database engine
Database engine
Status
Active
Active
Developer
Apache Software Foundation
ClickHouse, Inc.
First release
2016
2016
Latest version
1.18.1 (Jan 9, 2026)
26.10.2.103 (Oct 24, 2026)
License
Open source (permissive)Apache License 2.0
Open source (permissive)Apache License 2.0
Free tier
✓
✓
popularity
WhichDB Score
18.6
69.8
Rank
#176
#10
GitHub stars
1.9K
50.6K
Stack Overflow questions
130
2.2K
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Massive (Multi-PB)
Horizontal scaling
Native
Native
Multi-region
None
Read replicas
ACID
Limited
Limited
Consistency
Strong
Eventual
Schema
Strict
Strict
Architecture
Distributed
Distributed, Shared storage, Single node, Client server
deployment
Self-hosted
✓
✓
Vendor-managed cloud
—
✓
Serverless
—
✓
Embedded
—
—
Edge
—
—
Clouds
–
AWS, Google Cloud, Azure, Alibaba Cloud, Tencent Cloud, Aiven
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
Impala SQL, Spark SQL, Kudu client API
SQL (ClickHouse dialect), PRQL, KQL (experimental)
Client languages
C++, Java, Python
Python, Go, Java, JavaScript, Rust, C++, C#
Best for
Real-time analytics, OLAP, Time-series
Real-time analytics, OLAP, Observability, Warehouse

Apache Kudu vs ClickHouse: FAQ

What is the difference between Apache Kudu and ClickHouse?

Apache Kudu: Columnar storage engine for fast analytics on fast-changing data, paired with Impala or Spark. ClickHouse: Open-source columnar OLAP database known for very fast aggregations over billions of rows. ClickHouse is built for larger datasets (Multi-PB) than Apache Kudu (≤ 1 PB). Only ClickHouse has joins, secondary indexes, full-text search, vector search, geospatial. ClickHouse has a serverless option; Apache Kudu does not.

When should I choose Apache Kudu over ClickHouse?

Choose Apache Kudu for mutable fact tables in Cloudera, near-real-time analytics with Impala and time-series with updates. Choose ClickHouse for product and web analytics; log and observability backends; and real-time dashboards over event streams.

Is Apache Kudu or ClickHouse more popular?

ClickHouse ranks #10 on the WhichDB Score (69.8/100) and Apache Kudu ranks #176 (18.6/100). Popularity is not fit: check the requirements that matter for your project.

Are Apache Kudu and ClickHouse open source?

Yes. Apache Kudu is open source. License: Apache License 2.0. Yes. ClickHouse is open source. License: Apache License 2.0.