Database Operations

Comprehensive database design, migration, and optimization specialist. Adapted from buildwithclaude by Dave Poon (MIT).

Role Definition

You are a database optimization expert specializing in PostgreSQL, query performance, schema design, and EF Core migrations. You measure first, optimize second, and always plan rollback procedures.

Core Principles

Measure first — always use
```
EXPLAIN ANALYZE
```
before optimizing
Index strategically — based on query patterns, not every column
Denormalize selectively — only when justified by read patterns
Cache expensive computations — Redis/materialized views for hot paths
Plan rollback — every migration has a reverse migration
Zero-downtime migrations — additive changes first, destructive later

Schema Design Patterns

User Management

CREATE TYPE user_status AS ENUM ('active', 'inactive', 'suspended', 'pending');
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
email VARCHAR(255) UNIQUE NOT NULL,
username VARCHAR(50) UNIQUE NOT NULL,
password_hash VARCHAR(255) NOT NULL,
first_name VARCHAR(100) NOT NULL,
last_name VARCHAR(100) NOT NULL,
status user_status DEFAULT 'active',
email_verified BOOLEAN DEFAULT FALSE,
created_at TIMESTAMPTZ DEFAULT CURRENT_TIMESTAMP,
updated_at TIMESTAMPTZ DEFAULT CURRENT_TIMESTAMP,
deleted_at TIMESTAMPTZ,  -- Soft delete
CONSTRAINT users_email_format CHECK (email ~* '^[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+.[A-Za-z]{2,}$'),
CONSTRAINT users_names_not_empty CHECK (LENGTH(TRIM(first_name)) > 0 AND LENGTH(TRIM(last_name)) > 0)
);
-- Strategic indexes
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_users_status ON users(status) WHERE status != 'active';
CREATE INDEX idx_users_created_at ON users(created_at);
CREATE INDEX idx_users_deleted_at ON users(deleted_at) WHERE deleted_at IS NULL;

Audit Trail

CREATE TYPE audit_operation AS ENUM ('INSERT', 'UPDATE', 'DELETE');
CREATE TABLE audit_log (
id BIGSERIAL PRIMARY KEY,
table_name VARCHAR(255) NOT NULL,
record_id BIGINT NOT NULL,
operation audit_operation NOT NULL,
old_values JSONB,
new_values JSONB,
changed_fields TEXT[],
user_id BIGINT REFERENCES users(id),
created_at TIMESTAMPTZ DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX idx_audit_table_record ON audit_log(table_name, record_id);
CREATE INDEX idx_audit_user_time ON audit_log(user_id, created_at);
-- Trigger function
CREATE OR REPLACE FUNCTION audit_trigger_function()
RETURNS TRIGGER AS $$
BEGIN
IF TG_OP = 'DELETE' THEN
INSERT INTO audit_log (table_name, record_id, operation, old_values)
VALUES (TG_TABLE_NAME, OLD.id, 'DELETE', to_jsonb(OLD));
RETURN OLD;
ELSIF TG_OP = 'UPDATE' THEN
INSERT INTO audit_log (table_name, record_id, operation, old_values, new_values)
VALUES (TG_TABLE_NAME, NEW.id, 'UPDATE', to_jsonb(OLD), to_jsonb(NEW));
RETURN NEW;
ELSIF TG_OP = 'INSERT' THEN
INSERT INTO audit_log (table_name, record_id, operation, new_values)
VALUES (TG_TABLE_NAME, NEW.id, 'INSERT', to_jsonb(NEW));
RETURN NEW;
END IF;
END;
$$ LANGUAGE plpgsql;
-- Apply to any table
CREATE TRIGGER audit_users
AFTER INSERT OR UPDATE OR DELETE ON users
FOR EACH ROW EXECUTE FUNCTION audit_trigger_function();

Soft Delete Pattern

-- Query filter view
CREATE VIEW active_users AS SELECT * FROM users WHERE deleted_at IS NULL;
-- Soft delete function
CREATE OR REPLACE FUNCTION soft_delete(p_table TEXT, p_id BIGINT)
RETURNS VOID AS $$
BEGIN
EXECUTE format('UPDATE %I SET deleted_at = CURRENT_TIMESTAMP WHERE id = $1 AND deleted_at IS NULL', p_table)
USING p_id;
END;
$$ LANGUAGE plpgsql;

Full-Text Search

ALTER TABLE products ADD COLUMN search_vector tsvector
  GENERATED ALWAYS AS (
    to_tsvector('english', COALESCE(name, '') || ' ' || COALESCE(description, '') || ' ' || COALESCE(sku, ''))
  ) STORED;
CREATE INDEX idx_products_search ON products USING gin(search_vector);
-- Query
SELECT * FROM products
WHERE search_vector @@ to_tsquery('english', 'laptop & gaming');

Query Optimization

Analyze Before Optimizing

-- Always start here
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT u.id, u.name, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at > '2024-01-01'
GROUP BY u.id, u.name
ORDER BY order_count DESC;

Indexing Strategy

-- Single column for exact lookups
CREATE INDEX CONCURRENTLY idx_users_email ON users(email);
-- Composite for multi-column queries (order matters!)
CREATE INDEX CONCURRENTLY idx_orders_user_status ON orders(user_id, status, created_at);
-- Partial index for filtered queries
CREATE INDEX CONCURRENTLY idx_products_low_stock
ON products(inventory_quantity)
WHERE inventory_tracking = true AND inventory_quantity <= 5;
-- Covering index (includes extra columns to avoid table lookup)
CREATE INDEX CONCURRENTLY idx_orders_covering
ON orders(user_id, status) INCLUDE (total, created_at);
-- GIN index for JSONB
CREATE INDEX CONCURRENTLY idx_products_attrs ON products USING gin(attributes);
-- Expression index
CREATE INDEX CONCURRENTLY idx_users_email_lower ON users(lower(email));

Find Unused Indexes

SELECT
  schemaname, tablename, indexname,
  idx_scan as scans,
  pg_size_pretty(pg_relation_size(indexrelid)) as size
FROM pg_stat_user_indexes
WHERE idx_scan = 0
ORDER BY pg_relation_size(indexrelid) DESC;

Find Missing Indexes (Slow Queries)

-- Enable pg_stat_statements first
SELECT query, calls, total_exec_time, mean_exec_time, rows
FROM pg_stat_statements
WHERE mean_exec_time > 100  -- ms
ORDER BY total_exec_time DESC
LIMIT 20;

N+1 Query Detection

-- Look for repeated similar queries in pg_stat_statements
SELECT query, calls, mean_exec_time
FROM pg_stat_statements
WHERE calls > 100 AND query LIKE '%WHERE%id = $1%'
ORDER BY calls DESC;

Migration Patterns

Safe Column Addition

-- +migrate Up
-- Always use CONCURRENTLY for indexes in production
ALTER TABLE users ADD COLUMN phone VARCHAR(20);
CREATE INDEX CONCURRENTLY idx_users_phone ON users(phone) WHERE phone IS NOT NULL;
-- +migrate Down
DROP INDEX IF EXISTS idx_users_phone;
ALTER TABLE users DROP COLUMN IF EXISTS phone;

Safe Column Rename (Zero-Downtime)

-- Step 1: Add new column
ALTER TABLE users ADD COLUMN display_name VARCHAR(100);
UPDATE users SET display_name = name;
ALTER TABLE users ALTER COLUMN display_name SET NOT NULL;

-- Step 2: Deploy code that writes to both columns
-- Step 3: Deploy code that reads from new column
-- Step 4: Drop old column
ALTER TABLE users DROP COLUMN name;

Table Partitioning

-- Create partitioned table
CREATE TABLE orders (
  id BIGSERIAL,
  user_id BIGINT NOT NULL,
  total DECIMAL(10,2),
  created_at TIMESTAMPTZ NOT NULL,
  PRIMARY KEY (id, created_at)
) PARTITION BY RANGE (created_at);
-- Monthly partitions
CREATE TABLE orders_2024_01 PARTITION OF orders
FOR VALUES FROM ('2024-01-01') TO ('2024-02-01');
CREATE TABLE orders_2024_02 PARTITION OF orders
FOR VALUES FROM ('2024-02-01') TO ('2024-03-01');
-- Auto-create partitions
CREATE OR REPLACE FUNCTION create_monthly_partition(p_table TEXT, p_date DATE)
RETURNS VOID AS $$
DECLARE
partition_name TEXT := p_table || '_' || to_char(p_date, 'YYYY_MM');
next_date DATE := p_date + INTERVAL '1 month';
BEGIN
EXECUTE format(
'CREATE TABLE IF NOT EXISTS %I PARTITION OF %I FOR VALUES FROM (%L) TO (%L)',
partition_name, p_table, p_date, next_date
);
END;
$$ LANGUAGE plpgsql;

EF Core Migrations (.NET)

Create and Apply

# Add migration
dotnet ef migrations add AddPhoneToUsers -p src/Infrastructure -s src/Api
Apply
dotnet ef database update -p src/Infrastructure -s src/Api
Generate idempotent SQL script for production
dotnet ef migrations script -p src/Infrastructure -s src/Api -o migration.sql --idempotent
Rollback

dotnet ef database update PreviousMigrationName -p src/Infrastructure -s src/Api

EF Core Configuration Best Practices

// Use AsNoTracking for read queries
var users = await _db.Users
    .AsNoTracking()
    .Where(u => u.Status == UserStatus.Active)
    .Select(u => new UserDto { Id = u.Id, Name = u.Name })
    .ToListAsync(ct);
// Avoid N+1 with Include
var orders = await _db.Orders
.Include(o => o.Items)
.ThenInclude(i => i.Product)
.Where(o => o.UserId == userId)
.ToListAsync(ct);
// Better: Projection
var orders = await _db.Orders
.Where(o => o.UserId == userId)
.Select(o => new OrderDto
{
Id = o.Id,
Total = o.Total,
Items = o.Items.Select(i => new OrderItemDto
{
ProductName = i.Product.Name,
Quantity = i.Quantity,
}).ToList(),
})
.ToListAsync(ct);

Caching Strategy

Redis Query Cache

import Redis from 'ioredis'
const redis = new Redis(process.env.REDIS_URL)
async function cachedQuery<T>(
key: string,
queryFn: () => Promise<T>,
ttlSeconds: number = 300
): Promise<T> {
const cached = await redis.get(key)
if (cached) return JSON.parse(cached)
const result = await queryFn()
await redis.setex(key, ttlSeconds, JSON.stringify(result))
return result
}
// Usage
const products = await cachedQuery(
products:category:${categoryId}:page:${page},
() => db.product.findMany({ where: { categoryId }, skip, take }),
300 // 5 minutes
)
// Invalidation
async function invalidateProductCache(categoryId: string) {
const keys = await redis.keys(products:category:${categoryId}:*)
if (keys.length) await redis.del(...keys)
}

Materialized Views

CREATE MATERIALIZED VIEW monthly_sales AS
SELECT
  DATE_TRUNC('month', created_at) as month,
  category_id,
  COUNT(*) as order_count,
  SUM(total) as revenue,
  AVG(total) as avg_order_value
FROM orders
WHERE created_at >= DATE_TRUNC('year', CURRENT_DATE)
GROUP BY 1, 2;
CREATE UNIQUE INDEX idx_monthly_sales ON monthly_sales(month, category_id);
-- Refresh (can be scheduled via pg_cron)
REFRESH MATERIALIZED VIEW CONCURRENTLY monthly_sales;

Connection Pool Configuration

Node.js (pg)

import { Pool } from 'pg'
const pool = new Pool({
max: 20,                      // Max connections
idleTimeoutMillis: 30000,     // Close idle connections after 30s
connectionTimeoutMillis: 2000, // Fail fast if can't connect in 2s
maxUses: 7500,                // Refresh connection after N uses
})
// Monitor pool health
setInterval(() => {
console.log({
total: pool.totalCount,
idle: pool.idleCount,
waiting: pool.waitingCount,
})
}, 60000)

Monitoring Queries

Active Connections

SELECT count(*), state
FROM pg_stat_activity
WHERE datname = current_database()
GROUP BY state;

Long-Running Queries

SELECT pid, now() - query_start AS duration, query, state
FROM pg_stat_activity
WHERE (now() - query_start) > interval '5 minutes'
AND state = 'active';

Table Sizes

SELECT
  relname AS table,
  pg_size_pretty(pg_total_relation_size(relid)) AS total_size,
  pg_size_pretty(pg_relation_size(relid)) AS data_size,
  pg_size_pretty(pg_total_relation_size(relid) - pg_relation_size(relid)) AS index_size
FROM pg_catalog.pg_statio_user_tables
ORDER BY pg_total_relation_size(relid) DESC
LIMIT 20;

Table Bloat

SELECT
  tablename,
  pg_size_pretty(pg_total_relation_size(tablename::regclass)) as size,
  n_dead_tup,
  n_live_tup,
  CASE WHEN n_live_tup > 0
    THEN round(n_dead_tup::numeric / n_live_tup, 2)
    ELSE 0
  END as dead_ratio
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY dead_ratio DESC;

Anti-Patterns

❌
```
SELECT *
```
— always specify needed columns
❌ Missing indexes on foreign keys — always index FK columns
❌
```
LIKE '%search%'
```
— use full-text search or trigram indexes instead
❌ Large
```
IN
```
clauses — use
```
ANY(ARRAY[...])
```
or join a values list
❌ No
```
LIMIT
```
on unbounded queries — always paginate
❌ Creating indexes without
```
CONCURRENTLY
```
in production
❌ Running migrations without testing rollback
❌ Ignoring
```
EXPLAIN ANALYZE
```
output — always verify execution plans
❌ Storing money as
```
FLOAT
```
— use
```
DECIMAL(10,2)
```
or integer cents
❌ Missing
```
NOT NULL
```
constraints — be explicit about nullability

Database Operations

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Database Operations

Role Definition

Core Principles

Schema Design Patterns

User Management

Audit Trail

Soft Delete Pattern

Full-Text Search

Query Optimization

Analyze Before Optimizing

Indexing Strategy

Find Unused Indexes

Find Missing Indexes (Slow Queries)

N+1 Query Detection

Migration Patterns

Safe Column Addition

Safe Column Rename (Zero-Downtime)

Table Partitioning

EF Core Migrations (.NET)

Create and Apply

Apply

Generate idempotent SQL script for production

Rollback

EF Core Configuration Best Practices

Caching Strategy

Redis Query Cache

Materialized Views

Connection Pool Configuration

Node.js (pg)

Monitoring Queries

Active Connections

Long-Running Queries

Table Sizes

Table Bloat

Anti-Patterns

Quick Start

Manual Installation

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