ClickHouse alternatives

4 tools to consider instead of ClickHouse, shown against it.

ClickHouse Apache Druid Apache Pinot StarRocks Apache Doris
Vendor ClickHouse, Inc. Apache Software Foundation Apache Software Foundation StarRocks (Linux Foundation project; commercial backing from CelerData) Apache Software Foundation
Pricing model Open source + paid options Open source + paid options Open source + paid options Open source + paid options Open source + paid options
Free tier Yes Yes Yes Yes Yes
Deployment Cloud, Self-hosted Self-hosted Self-hosted Self-hosted Self-hosted
Open source Yes (Apache-2.0) Yes (Apache-2.0) Yes (Apache-2.0) Yes (Apache-2.0) Yes (Apache-2.0)
Best for Engineering teams building real-time dashboards or log/event analytics who want maximum query throughput on commodity hardware. Teams building user-facing or operational dashboards over continuously streaming event data. Teams embedding low-latency, high-concurrency analytics directly into customer-facing products. Teams wanting a single fast SQL engine across both freshly loaded data and existing lakehouse tables. Teams wanting one MPP engine for both real-time dashboards and ad hoc SQL reporting.
Pricing

The self-hosted database is free open source; the managed ClickHouse Cloud service is billed separately (see clickhouse-cloud).

Pricing has not been verified yet — see the vendor's site.

Free and open source under the Apache Software Foundation; commercial managed hosting is available separately through Imply.

Pricing has not been verified yet — see the vendor's site.

Free and open source under the Apache Software Foundation; commercial managed hosting is available separately through StarTree.

Pricing has not been verified yet — see the vendor's site.

Free and open source; a commercial managed cloud version is offered separately by CelerData.

Pricing has not been verified yet — see the vendor's site.

Free and open source under the Apache Software Foundation; a commercial cloud version is offered separately by SelectDB.

Pricing has not been verified yet — see the vendor's site.

Features
  • Columnar storage with vectorized execution
  • Sub-second aggregate queries over billions of rows
  • Materialized views for pre-aggregation
  • Native Kafka, S3 and MySQL/Postgres table engines
  • High compression ratios via column-level codecs
  • Distributed sharding and replication
  • Standard SQL dialect with array and JSON extensions
  • Real-time streaming ingestion from Kafka/Kinesis
  • Columnar storage with bitmap indexing
  • Sub-second query response on high-cardinality data
  • Native JSON query language and Druid SQL
  • Automatic data rollup and retention rules
  • Multi-tenant query and ingestion isolation
  • Approximate algorithms for count-distinct and quantiles
  • Real-time and batch ingestion (Kafka, S3, HDFS)
  • Per-column pluggable indexing (inverted, sorted, star-tree)
  • Millisecond query latency at high concurrency
  • SQL query interface
  • Upsert support for mutable data
  • Horizontal scaling of controller/broker/server tiers
  • Anomaly detection via ThirdEye integration
  • Vectorized execution with cost-based optimizer
  • Query federation across Iceberg, Hudi, Delta Lake and Hive
  • Materialized views that accelerate lakehouse queries
  • MySQL wire-protocol compatibility
  • Real-time streaming ingestion
  • Shared-data architecture separating compute and storage
  • Real-time streaming and micro-batch ingestion
  • MySQL wire-protocol compatibility
  • Federated queries over Hive, Iceberg and Hudi
  • Materialized views and automatic query rewrite
  • Vectorized execution engine
  • High-concurrency point lookups alongside large scans

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