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:

-- Define shard ranges
-- Shard 0: user_id 0-999999
-- Shard 1: user_id 1000000-1999999
-- Shard 2: user_id 2000000-2999999

CREATE TABLE users_shard_0 (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id BIGINT NOT NULL,
  email VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  CONSTRAINT shard_0_range CHECK (user_id BETWEEN 0 AND 999999)
);

CREATE TABLE users_shard_1 (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id BIGINT NOT NULL,
  email VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  CONSTRAINT shard_1_range CHECK (user_id BETWEEN 1000000 AND 1999999)
);

-- Function to determine shard
CREATE OR REPLACE FUNCTION get_shard_id(p_user_id BIGINT)
RETURNS INT AS $$
BEGIN
// ... (see reference guides for full implementation)

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