# ClickHouse

> Column-oriented OLAP database for real-time analytics

ClickHouse is an open-source columnar database designed for low-latency analytical queries over large volumes, available self-hosted or as ClickHouse Cloud.

Website: https://clickhouse.com

## Use it when

- Interactive analytics over large event volumes need sub-second scans: user-facing dashboards, observability, clickstream.
- Ingest is heavy and continuous, Kafka included, with materialized views maintaining aggregates at insert time.
- SQL depth matters: a rich analytical dialect, plus MySQL and PostgreSQL wire ports for existing tooling.
- You want an open-source engine with a first-party managed cloud when the operations should go away.

## Think twice when

- The workload is update-heavy; mutations rewrite whole parts, so OLTP-shaped change belongs elsewhere.
- Query-time joins across many large tables are the norm; StarRocks makes that its headline, and warehouses absorb it too.
- Extreme per-user query rates with strict SLAs are the entire product; Pinot and Druid are built around exactly that shape.

## How it runs

Self-hosted from a single node to replicated shards with Keeper coordinating, MergeTree tables on local disk; ClickHouse Cloud runs SharedMergeTree over object storage with autoscaling compute. Insert-trigger materialized views, refreshable views, and projections carry pre-aggregation. Iceberg and Delta are reachable through DataLakeCatalog.

## Details

### General

| Attribute | Value |
| --- | --- |
| License | Open source (permissive) |
| SPDX identifier | Apache-2.0 |
| Deployment | Self-hosted, Managed, Hybrid |
| Workload | Interactive, Streaming |
| Operational complexity | Medium |
| Pricing | Free, Subscription |
| Language | C++ |
| Repository | https://github.com/ClickHouse/ClickHouse |
| Documentation | https://clickhouse.com/docs |
| Stars | 50k |

### OLAP Engines

| Attribute | Value |
| --- | --- |
| Specialization | General-purpose column store for analytics, logs and observability |
| SQL dialect | ClickHouse SQL; MySQL and PostgreSQL wire ports |
| Joins | Distributed, several join algorithms |
| Updates and deletes | Lightweight UPDATE and DELETE; mutations rewrite parts |
| Ingest to queryable | Immediate on insert; async inserts not queryable until flush |
| Storage format | MergeTree; Iceberg and Delta via DataLakeCatalog |
| Compute and storage | MergeTree on local disk; SharedMergeTree over object storage in Cloud |
| Indexes | Sparse primary key; skipping indexes: minmax, set, bloom filter, text |
| Pre-aggregation | Materialized views as insert triggers; refreshable MVs and projections |
| Concurrent users | No fixed limit; concurrency traded against per-query parallelism |

## Capabilities

- [OLAP Engines](https://matca.io/capabilities/olap-engine)

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Source: https://matca.io/clickhouse
Last updated: 2026-08-31T11:40:49.655Z