Agent skill · data analytics · aj-geddes
database-sharding
Implement database sharding for horizontal scalability. Use when scaling large databases, distributing data across multiple servers, or designing sharded architectures.
Why this skill is useful
Provides specific sharding strategies and SQL examples that the AI wouldn't reliably generate on its own.
What it needs
About 1k tokens when loaded. Last updated 2026-03-04. 307 stars on the source repository.
What this skill does
Database Sharding Table of Contents Overview When to Use Quick Start Reference Guides Best Practices Overview Implement horizontal data partitioning across multiple database servers. Covers sharding strategies, consistent hashing, shard key selection, and cross-shard querying patterns. When to Use Database size exceeds single server capacity Read/write throughput needs horizontal scaling Geographic data distribution requirements Multi-tenant data isolation Cost optimization through distributed architecture Load balancing across database instances Quick Start Minimal working example: Reference Guides Detailed implementations in the references/ directory: Guide Contents --- --- Range-Based Sharding Range-Based Sharding Hash-Based Sharding Hash-Based Sharding Directory-Based Sharding Directory-Based Sharding Best Practices ✅ DO Follow established patterns and conventions Write clean, maintainable code Add appropriate documentation Test thoroughly before deploying ❌ DON'T Skip testing or validation Ignore error handling Hard-code configuration values
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aj-geddes/database-sharding