TroveGrid
Back to all tools
ClickHouse logo

ClickHouse

Real-time OLAP database — sub-second queries on billions of rows, open-source.

0Open Source
Data Warehouse
Official Website View on GitHub
Share:XLinkedInWhatsApp

Overview

ClickHouse is an open-source columnar OLAP database management system for real-time analytics, capable of processing billions of rows per second with sub-second query latency on terabytes of data.

Key Features

  • Columnar storage with LZ4/ZSTD compression for 10x storage efficiency
  • Vectorized query execution for extreme analytical throughput
  • MergeTree table engine family with partitioning and TTL
  • Materialized Views for pre-aggregating high-cardinality streams
  • Native Kafka and S3 integrations for real-time data ingestion
  • ClickHouse Cloud with auto-scaling and managed backups

Real-World Workflows

Real-time product analytics backend

  1. 1Stream click and event data from Kafka into ClickHouse via Kafka table engine
  2. 2Create Materialized Views to pre-aggregate per-page and per-user metrics
  3. 3Query aggregates with sub-second latency from a Grafana or Superset dashboard
  4. 4Use ReplicatedMergeTree for high availability across availability zones

Log analytics at scale

  1. 1Ingest application logs from Filebeat or Vector into ClickHouse
  2. 2Use the Log table engine with TTL to auto-expire old logs
  3. 3Query log patterns and error rates with SQL in seconds
  4. 4Build a Grafana dashboard on top of ClickHouse for live log analytics

Getting Started

# Start ClickHouse with Docker
docker run -d --name clickhouse \
  -p 8123:8123 -p 9000:9000 \
  clickhouse/clickhouse-server

# Connect via HTTP API
curl 'http://localhost:8123/?query=SELECT+1'

# Or use clickhouse-client
docker exec -it clickhouse clickhouse-client

Compare Alternatives

See how ClickHouse stacks up against similar tools.

VSsnowflakeVSdatabricksVSduckdbVSdruid