Skill UI

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

A comprehensive skill for optimizing complex SQL queries, designing robust database schemas, and troubleshooting performance bottlenecks across various dialects (PostgreSQL, MySQL, etc.). Use this when queries are slow, complex set-based logic is needed (CTEs, Window Functions), or when structuring/migrating a database schema. It provides detailed query plan analysis, advanced indexing strategies, and industry best practices.

A comprehensive guide to high-performance analytical database patterns using ClickHouse. Covers advanced topics including MergeTree engine types (Replacing, Aggregating), efficient query optimization techniques (filtering, window functions), bulk data insertion strategies, and setting up materialized views for real-time analytics. Ideal for data engineers and analysts building OLAP systems.

Add distributed rate limiting to API routes, middleware, and edge functions with @upstash/ratelimit and Upstash Redis. Covers sliding window, fixed window, and token bucket algorithms, per-identifier keys, and returning 429 with Retry-After headers.