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ClickHouse

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by ClickHouse, Inc. · Database · also known as chDB, clickhouse-local

Open-source columnar OLAP database server for fast aggregations over billions of rows, with MergeTree storage, SQL and a managed ClickHouse Cloud

Apache-2.0 licenseOpen sourceFreeUsage-basedEnterpriseSelf-hostedCloudLocalSelf-hostable
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Link verified Nov 2, 2026

Overview

ClickHouse is an open-source column-oriented database management system developed by ClickHouse, Inc. under Apache 2.0, originally built at Yandex for web analytics. Its MergeTree family of table engines stores sorted, compressed column parts with sparse primary indexes and skipping indexes, and the vectorized SQL engine aggregates billions of rows per second on a single server, with distributed tables, replication via ClickHouse Keeper and sharding for clusters. Beyond native tables it queries external data through table functions for S3, HTTP, PostgreSQL, MySQL, Kafka and files in Parquet, CSV, JSON and dozens of other formats, and materialized views transform data on insert. clickhouse-local runs the same engine from the command line over local files, and chDB embeds it in Python, Node, Go and Rust processes.

Typical workloads are event analytics, observability (logs, traces, metrics), time-series and financial tick data, and serving dashboards from Grafana, Metabase or Superset over HTTP or the native protocol with clients in most languages. ClickHouse Cloud is the managed service with separated storage and compute; many teams self-host a single node on Linux or in Docker, including on Apple Silicon.

The design optimizes append-heavy, read-mostly analytics: updates and deletes run as asynchronous mutations, there are no multi-statement transactions in the OLTP sense, joins of large tables need memory and care, and the SQL dialect has its own functions and behaviors that differ from PostgreSQL. Small point lookups and frequent single-row inserts should be batched or routed elsewhere.

Capabilities

  • Columnar MergeTree storage with compression and sparse indexes
  • Vectorized SQL execution with parallel aggregation
  • Replication and sharding via ClickHouse Keeper and distributed tables
  • Table functions for S3, HTTP, PostgreSQL, MySQL, Kafka and local files
  • Materialized views and projections for on-insert transformation
  • Reads and writes Parquet, CSV, JSON, Arrow and many other formats
  • clickhouse-local CLI and chDB embedded engine
  • HTTP and native protocol clients for Python, Go, Java, JavaScript, Rust and more

Typical workflows

  1. Store and aggregate tick or minute-bar data across years
  2. Log and trace analytics behind Grafana dashboards
  3. Query Parquet files on S3 directly with table functions
  4. Serve product analytics dashboards from Metabase or Superset

Strengths

  • Very fast analytical scans on a single node
  • Apache 2.0 and self-hostable
  • Broad format and external-source support
  • Managed cloud option

Limitations

  • Updates and deletes are asynchronous mutations
  • No OLTP-style transactions
  • Large joins are memory-intensive
  • Dialect differences from standard PostgreSQL SQL

Prerequisites

  • A Linux server, Docker or macOS binary, or a ClickHouse Cloud account

Who it is for

  • Data engineers
  • Observability and product-analytics teams
  • Quantitative researchers with large time series

Alternatives & comparison

DuckDB offers a similar columnar, vectorized engine but in-process and single-user, whereas ClickHouse is a networked server with replication and sharding. Spark and Trino are distributed query engines over external storage rather than storage engines themselves. TimescaleDB keeps time-series data inside PostgreSQL with full transactions at lower scan speed. Elasticsearch addresses log analytics through inverted indexes and a JSON DSL instead of columnar SQL.

  • Apache Spark

    Distributed data processing engine with DataFrame and SQL APIs in Python, Scala, Java and R, plus structured streaming and MLlib

    Open sourceOpen source
  • DuckDB

    In-process analytical SQL database that queries Parquet, CSV and Arrow data directly from Python, R, Node or the CLI

    Open sourceOpen source
  • Elasticsearch

    Distributed search and analytics engine on Apache Lucene with full-text, aggregations, vector search and ES|QL; triple-licensed AGPL, SSPL and Elastic License

    MixedOpen source
  • OpenSearch

    Apache-2.0 search and analytics suite forked from Elasticsearch and Kibana, governed by the OpenSearch Software Foundation

    Open sourceOpen source
  • PostgreSQL

    Open-source object-relational database server with a large extension ecosystem (PostGIS, pgvector, TimescaleDB) and broad SQL coverage

    Open sourceOpen source
  • Prometheus

    Pull-based metrics monitoring system and time-series database with the PromQL query language, service discovery and the Alertmanager component

    Open sourceOpen source
  • TimescaleDB

    PostgreSQL extension for time-series data adding hypertables, compression and continuous aggregates, from the company now named Tiger Data

    MixedOpen source
  • Trino

    Distributed SQL query engine that federates queries across data lakes, warehouses and databases through connectors, formerly PrestoSQL

    Open sourceOpen source
Compare ClickHouse with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

  • License
    ClickHouse LICENSE (Apache 2.0)

    https://github.com/ClickHouse/ClickHouse/blob/master/LICENSE

    Supports: license_spdx, source_model

    checked Nov 1, 2026
  • Official documentation
    ClickHouse Docs

    https://clickhouse.com/docs

    Supports: capabilities, data_formats, languages

    checked Nov 1, 2026
  • Official site
    ClickHouse

    https://clickhouse.com/

    Supports: name, summary, vendor

    checked Nov 1, 2026
  • Pricing page
    ClickHouse Cloud pricing

    https://clickhouse.com/pricing

    Supports: pricing_model

    checked Nov 1, 2026
  • Repository
    ClickHouse/ClickHouse

    https://github.com/ClickHouse/ClickHouse

    Supports: repo_url

    checked Nov 1, 2026
Confidence
High
Reviewed
Nov 1, 2026
Links
Verified · Nov 2, 2026

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