clickhouse-io

Installation
Summary

ClickHouse table design, query optimization, and analytics patterns for high-performance OLAP workloads.

  • Covers three primary MergeTree engine variants: standard MergeTree for time-series data, ReplacingMergeTree for deduplication, and AggregatingMergeTree for pre-aggregated metrics
  • Includes query optimization patterns for efficient filtering, aggregations, window functions, and percentile calculations with ClickHouse-specific functions
  • Demonstrates data insertion strategies (bulk inserts, streaming), materialized views for real-time aggregations, and performance monitoring via system tables
  • Provides ready-to-use patterns for common analytics workflows: time-series analysis, retention, funnels, cohorts, and ETL/CDC pipelines with TypeScript examples
SKILL.md

ClickHouse Analytics Patterns

ClickHouse-specific patterns for high-performance analytics and data engineering.

When to Activate

  • Designing ClickHouse table schemas (MergeTree engine selection)
  • Writing analytical queries (aggregations, window functions, joins)
  • Optimizing query performance (partition pruning, projections, materialized views)
  • Ingesting large volumes of data (batch inserts, Kafka integration)
  • Migrating from PostgreSQL/MySQL to ClickHouse for analytics
  • Implementing real-time dashboards or time-series analytics

Overview

ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP). It's optimized for fast analytical queries on large datasets.

Key Features:

  • Column-oriented storage
Related skills
Installs
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GitHub Stars
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First Seen
Jan 22, 2026