Source profileQuality 83/100

majiayu000/spellbook/skills/database-patterns/SKILL.md

database-patterns

Use when designing PostgreSQL + Redis data models, indexes, caching strategies, JSONB usage, tiered storage, or cache consistency contracts.

Source repository stars
249
Declared platforms
0
Static risk flags
0
Last source update
2026-08-02
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Use when designing PostgreSQL + Redis data models, indexes, caching strategies, JSONB usage, tiered storage, or cache consistency contracts.

Best for

  • Use when designing PostgreSQL + Redis data models, indexes, caching strategies, JSONB usage, tiered storage, or cache consistency contracts.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/majiayu000/spellbook --skill "skills/database-patterns"
Safe inspection promptEditorial

Inspect the Agent Skill "database-patterns" from https://github.com/majiayu000/spellbook/blob/01c5d88b0139a80ac38bfe7206ea99f28b0fc999/skills/database-patterns/SKILL.md at commit 01c5d88b0139a80ac38bfe7206ea99f28b0fc999. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    JSONB Usage

    Review the “JSONB Usage” section in the pinned source before continuing.

    Review and apply the “JSONB Usage” source section.
  2. 02

    Core Principles

    PostgreSQL Primary — Relational data, transactions, complex queries

    PostgreSQL Primary — Relational data, transactions, complex queriesRedis Secondary — Caching, sessions, real-time dataIndex-First Design — Design queries before indexes
  3. 03

    PostgreSQL

    Review the “PostgreSQL” section in the pinned source before continuing.

    Review and apply the “PostgreSQL” source section.
  4. 04

    Data Type Selection

    Review the “Data Type Selection” section in the pinned source before continuing.

    Review and apply the “Data Type Selection” source section.
  5. 05

    Schema Design

    Review the “Schema Design” section in the pinned source before continuing.

    Review and apply the “Schema Design” source section.

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score83/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars249SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
majiayu000/spellbook
Skill path
skills/database-patterns/SKILL.md
Commit
01c5d88b0139a80ac38bfe7206ea99f28b0fc999
License
MIT
Collected
2026-08-04
Default branch
main
View the original SKILL.md

Database Patterns

Core Principles

  • PostgreSQL Primary — Relational data, transactions, complex queries
  • Redis Secondary — Caching, sessions, real-time data
  • Index-First Design — Design queries before indexes
  • JSONB Sparingly — Structured data prefers columns
  • Cache-Aside Default — Read-through, write-around
  • Tiered Storage — Hot/Warm/Cold data separation
  • No backwards compatibility — Migrate data, don't keep legacy schemas

PostgreSQL

Data Type Selection

Use CaseTypeAvoid
Primary KeyUUID / BIGSERIALINT (range limits)
TimestampsTIMESTAMPTZTIMESTAMP (no timezone)
MoneyNUMERIC(19,4)FLOAT (precision loss)
StatusTEXT + CHECKINT (unreadable)
Semi-structuredJSONBJSON (no indexing)
Full-textTSVECTORLIKE '%..%'

Schema Design

-- Use UUID for distributed-friendly IDs
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
  email TEXT UNIQUE NOT NULL,
  name TEXT NOT NULL,
  status TEXT NOT NULL DEFAULT 'active'
    CHECK (status IN ('active', 'inactive', 'suspended')),
  metadata JSONB DEFAULT '{}',
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);

-- Updated timestamp trigger
CREATE OR REPLACE FUNCTION update_updated_at()
RETURNS TRIGGER AS $$
BEGIN
  NEW.updated_at = NOW();
  RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER users_updated_at
  BEFORE UPDATE ON users
  FOR EACH ROW
  EXECUTE FUNCTION update_updated_at();

Indexing Strategy

-- B-Tree: Equality, range, sorting (default)
CREATE INDEX idx_users_email ON users(email);

-- Composite: Leftmost prefix rule
-- Supports: (user_id), (user_id, created_at)
-- Does NOT support: (created_at) alone
CREATE INDEX idx_orders_user_date ON orders(user_id, created_at DESC);

-- Partial: Reduce index size
CREATE INDEX idx_active_users ON users(email)
  WHERE status = 'active';

-- GIN for JSONB: Containment queries
CREATE INDEX idx_metadata ON users USING GIN (metadata jsonb_path_ops);

-- Expression: Specific JSONB field
CREATE INDEX idx_user_role ON users ((metadata->>'role'));

-- Full-text search
CREATE INDEX idx_search ON products USING GIN (to_tsvector('english', name || ' ' || description));

JSONB Usage

-- Good: Dynamic attributes, rarely queried fields
CREATE TABLE products (
  id UUID PRIMARY KEY,
  name TEXT NOT NULL,
  price NUMERIC(19,4) NOT NULL,
  category TEXT NOT NULL,           -- Extracted: frequently queried
  attributes JSONB DEFAULT '{}'     -- Dynamic: color, size, specs
);

-- Query with containment
SELECT * FROM products
WHERE category = 'electronics'              -- B-Tree index
  AND attributes @> '{"brand": "Apple"}';   -- GIN index

-- Query specific field
SELECT * FROM products
WHERE attributes->>'color' = 'black';       -- Expression index

-- Update JSONB field
UPDATE products
SET attributes = attributes || '{"featured": true}'
WHERE id = '...';

Query Optimization

-- Always use EXPLAIN ANALYZE
EXPLAIN ANALYZE
SELECT u.*, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON o.user_id = u.id
WHERE u.status = 'active'
GROUP BY u.id
ORDER BY u.created_at DESC
LIMIT 20;

-- Watch for:
-- ❌ Seq Scan on large tables → Add index
-- ❌ Sort → Use index for ordering
-- ❌ Nested Loop with many rows → Consider JOIN order
-- ❌ Hash Join on huge tables → Add indexes

Connection Pooling

// PgBouncer or built-in pool
import { Pool } from 'pg';

const pool = new Pool({
  max: 20,                      // Max connections
  idleTimeoutMillis: 30000,     // Close idle connections
  connectionTimeoutMillis: 2000, // Fail fast
});

// Connection count formula:
// connections = (cores * 2) + effective_spindle_count
// Usually 10-30 is enough

Redis

Data Structure Selection

Use CaseStructureExample
Cache objectsStringuser:123 → JSON
CountersString + INCRviews:article:456
SessionsHashsession:abc → {userId, ...}
LeaderboardsSorted Setscores → {userId: score}
QueuesList/Streamtasks → LPUSH/RPOP
Unique setsSetonline_users
Real-timePub/Sub/StreamNotifications

Key Naming

# Format: <entity>:<id>:<attribute>
user:123:profile
user:123:settings
order:456:items
session:abc123

# Use colons for hierarchy
# Enables pattern matching with SCAN
SCAN 0 MATCH "user:*:profile" COUNT 100

TTL Strategy

const TTL = {
  SESSION: 24 * 60 * 60,      // 24 hours
  CACHE: 15 * 60,             // 15 minutes
  RATE_LIMIT: 60,             // 1 minute
  LOCK: 30,                   // 30 seconds
};

// Set with TTL
await redis.set(`cache:user:${id}`, JSON.stringify(user), 'EX', TTL.CACHE);

// Check TTL
const remaining = await redis.ttl(`cache:user:${id}`);

Caching Patterns

Cache-Aside (Lazy Loading)

async function getUser(id: string): Promise<User> {
  const cacheKey = `user:${id}`;

  // 1. Check cache
  const cached = await redis.get(cacheKey);
  if (cached) {
    return JSON.parse(cached);
  }

  // 2. Cache miss → Query database
  const user = await db.user.findUnique({ where: { id } });
  if (!user) {
    throw new NotFoundError('User not found');
  }

  // 3. Populate cache
  await redis.set(cacheKey, JSON.stringify(user), 'EX', 900);

  return user;
}

Write-Through

async function updateUser(id: string, data: UpdateInput): Promise<User> {
  // 1. Update database
  const user = await db.user.update({
    where: { id },
    data,
  });

  // 2. Update cache immediately
  await redis.set(`user:${id}`, JSON.stringify(user), 'EX', 900);

  return user;
}

Cache Invalidation

async function deleteUser(id: string): Promise<void> {
  // 1. Delete from database
  await db.user.delete({ where: { id } });

  // 2. Invalidate cache
  await redis.del(`user:${id}`);

  // 3. Invalidate related caches
  const keys = await redis.keys(`user:${id}:*`);
  if (keys.length > 0) {
    await redis.del(...keys);
  }
}

Cache Stampede Prevention

async function getUserWithLock(id: string): Promise<User> {
  const cacheKey = `user:${id}`;
  const lockKey = `lock:user:${id}`;

  // Check cache
  const cached = await redis.get(cacheKey);
  if (cached) {
    return JSON.parse(cached);
  }

  // Try to acquire lock
  const acquired = await redis.set(lockKey, '1', 'EX', 10, 'NX');

  if (!acquired) {
    // Another process is loading, wait and retry
    await sleep(100);
    return getUserWithLock(id);
  }

  try {
    // Double-check cache (another process might have populated it)
    const rechecked = await redis.get(cacheKey);
    if (rechecked) {
      return JSON.parse(rechecked);
    }

    // Load from database
    const user = await db.user.findUnique({ where: { id } });
    await redis.set(cacheKey, JSON.stringify(user), 'EX', 900);
    return user;
  } finally {
    await redis.del(lockKey);
  }
}

Cache Penetration Prevention

async function getUserSafe(id: string): Promise<User | null> {
  const cacheKey = `user:${id}`;

  const cached = await redis.get(cacheKey);

  // Check for cached null
  if (cached === 'NULL') {
    return null;
  }

  if (cached) {
    return JSON.parse(cached);
  }

  const user = await db.user.findUnique({ where: { id } });

  if (!user) {
    // Cache null with short TTL
    await redis.set(cacheKey, 'NULL', 'EX', 60);
    return null;
  }

  await redis.set(cacheKey, JSON.stringify(user), 'EX', 900);
  return user;
}

Tiered Storage

┌─────────────────────────────────────────────────┐
│                   Application                    │
└─────────────────────────────────────────────────┘
                        │
        ┌───────────────┼───────────────┐
        ▼               ▼               ▼
   ┌─────────┐    ┌─────────┐    ┌─────────┐
   │  Redis  │    │ Postgres │    │ Archive │
   │  (Hot)  │    │  (Warm)  │    │  (Cold) │
   └─────────┘    └─────────┘    └─────────┘

   < 1ms          ~10ms           ~100ms+
   Active data    Recent data     Historical
   Memory         SSD             Object storage

Partitioning for Cold Data

-- Partition by date range
CREATE TABLE orders (
  id UUID NOT NULL,
  user_id UUID NOT NULL,
  total NUMERIC(19,4) NOT NULL,
  created_at TIMESTAMPTZ NOT NULL
) PARTITION BY RANGE (created_at);

-- Create partitions
CREATE TABLE orders_2025_q1 PARTITION OF orders
  FOR VALUES FROM ('2025-01-01') TO ('2025-04-01');

CREATE TABLE orders_2025_q2 PARTITION OF orders
  FOR VALUES FROM ('2025-04-01') TO ('2025-07-01');

-- Archive old data
CREATE TABLE orders_archive (LIKE orders INCLUDING ALL);

-- Move old data to archive
WITH moved AS (
  DELETE FROM orders
  WHERE created_at < NOW() - INTERVAL '1 year'
  RETURNING *
)
INSERT INTO orders_archive SELECT * FROM moved;

Transactions

ACID Compliance

// Use transactions for multi-table operations
async function transferFunds(fromId: string, toId: string, amount: number) {
  await db.$transaction(async (tx) => {
    // Deduct from source
    const from = await tx.account.update({
      where: { id: fromId },
      data: { balance: { decrement: amount } },
    });

    if (from.balance < 0) {
      throw new Error('Insufficient funds');
    }

    // Add to destination
    await tx.account.update({
      where: { id: toId },
      data: { balance: { increment: amount } },
    });
  });
}

Optimistic Locking

-- Add version column
ALTER TABLE products ADD COLUMN version INT DEFAULT 1;

-- Update with version check
UPDATE products
SET
  stock = stock - 1,
  version = version + 1
WHERE id = $1 AND version = $2
RETURNING *;

-- If no rows returned, concurrent modification occurred

Checklist

## Schema
- [ ] UUID or BIGSERIAL for primary keys
- [ ] TIMESTAMPTZ for all timestamps
- [ ] NUMERIC for money, not FLOAT
- [ ] CHECK constraints for enums
- [ ] Foreign keys with ON DELETE

## Indexing
- [ ] Index for each WHERE clause pattern
- [ ] Composite indexes match query order
- [ ] GIN index for JSONB containment
- [ ] EXPLAIN ANALYZE for slow queries

## Caching
- [ ] Cache-aside as default pattern
- [ ] TTL on all cached data
- [ ] Cache invalidation on writes
- [ ] Stampede/penetration protection

## Operations
- [ ] Connection pooling configured
- [ ] Slow query logging enabled
- [ ] Backup and recovery tested
- [ ] Partition strategy for growth

See Also

Alternatives

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