What table engines does this skill support?

It covers the MergeTree family, including standard MergeTree for analytics, ReplacingMergeTree for deduplication, and AggregatingMergeTree for pre-calculated metrics.

Can this skill help with data ingestion issues?

Yes, it includes best practices for batch and stream insertions to avoid the performance degradation caused by small, frequent writes.

How does this skill improve ClickHouse query performance?

It provides specific patterns for column selection, index usage, and ClickHouse-native functions like quantile and uniq to maximize processing speed over large datasets.

Does it support real-time data processing?

Yes, it provides patterns for using Materialized Views for immediate aggregation and CDC (Change Data Capture) to sync data from sources like PostgreSQL.

ClickHouse Analytics & Engineering

Name: ClickHouse Analytics & Engineering
Author: Infopibe

byInfopibe

•

Database Management

Optimizes ClickHouse database performance with best-practice patterns for high-performance analytical workloads and data engineering.

This skill provides specialized guidance for ClickHouse, a high-performance columnar database designed for OLAP (Online Analytical Processing). It empowers Claude to implement efficient table designs using MergeTree engines, optimize complex analytical queries, and manage large-scale data ingestion via batch or streaming patterns. Whether you are building real-time dashboards, performing time-series analysis, or setting up materialized views for pre-aggregation, this skill ensures your ClickHouse implementation follows production-grade standards for speed and scalability.

Key Features

01High-performance query patterns for time-series and funnel analysis

02Performance monitoring and system log analysis

03Advanced MergeTree engine table design and optimization

04Efficient data ingestion strategies (Batch vs. Stream)

051 GitHub stars

06Real-time aggregation using Materialized Views

Use Cases

01Designing schema for high-volume log or event data

02Building automated ETL pipelines from PostgreSQL to ClickHouse

03Refactoring slow SQL queries for columnar performance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add infopibe/everything-claude-code clickhouse-io

For use in Claude.ai and ChatGPT

Key Features

01High-performance query patterns for time-series and funnel analysis

02Performance monitoring and system log analysis

03Advanced MergeTree engine table design and optimization

04Efficient data ingestion strategies (Batch vs. Stream)

051 GitHub stars

06Real-time aggregation using Materialized Views

Use Cases

01Designing schema for high-volume log or event data

02Building automated ETL pipelines from PostgreSQL to ClickHouse

03Refactoring slow SQL queries for columnar performance

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add infopibe/everything-claude-code clickhouse-io

For use in Claude.ai and ChatGPT