ClickHouse: Open-source column-oriented analytical database
Column-oriented database for real-time analytics with SQL support and distributed computing capabilities.
Learn more about ClickHouse
ClickHouse is an open-source column-oriented database management system built primarily in C++ with some Rust components. It stores data in columnar format and uses vectorized query execution to process analytical queries across distributed clusters. The system implements a massively parallel processing (MPP) architecture that can handle OLAP workloads and real-time analytics. ClickHouse is commonly used for business intelligence, log analysis, time-series data processing, and data warehousing applications.
Columnar Storage
Data is stored in column-oriented format rather than row-based, optimizing compression and query performance for analytical workloads. This architecture reduces I/O operations when processing queries that access specific columns.
Distributed Architecture
Supports horizontal scaling across multiple nodes with automatic data sharding and replication. Queries can be executed in parallel across the cluster for improved performance on large datasets.
Real-time Processing
Handles both batch and streaming data ingestion with low-latency query responses. The system can process and analyze data as it arrives without requiring separate ETL processes.
-- Create analytics events table
CREATE TABLE analytics.events (
event_id UUID DEFAULT generateUUIDv4(),
user_id UInt64,
event_type LowCardinality(String),
timestamp DateTime64(3) DEFAULT now64(),
properties Map(String, String),
session_id String,
page_url String,
user_agent String
) ENGINE = MergeTree()
PARTITION BY toYYYYMM(timestamp)
ORDER BY (event_type, timestamp, user_id);
-- Query for real-time analytics dashboard
SELECT
event_type,
count() as event_count,
uniq(user_id) as unique_users,
avg(toUnixTimestamp(timestamp)) as avg_timestamp
FROM analytics.events
WHERE timestamp >= now() - INTERVAL 1 HOUR
GROUP BY event_type
ORDER BY event_count DESC;See how people are using ClickHouse
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