🇺🇸English

PostgreSQL Best Practices

Core Principles

• Leverage PostgreSQL's advanced features for robust data modeling
• Optimize queries using EXPLAIN ANALYZE and proper indexing strategies
• Use native PostgreSQL data types appropriately
• Implement proper connection pooling and resource management
• Follow PostgreSQL-specific security best practices

Schema Design

Data Types

• Use appropriate native types: UUID, JSONB, ARRAY, INET, CIDR

• Prefer TIMESTAMPTZ over TIMESTAMP for timezone-aware applications

• Use TEXT instead of VARCHAR when no length limit is needed

• Consider NUMERIC for precise decimal calculations (financial data)

• Use SERIAL or BIGSERIAL for auto-incrementing IDs, or UUID for distributed systems

  CREATE TABLE orders ( order_id UUID PRIMARY KEY DEFAULT gen_random_uuid(), customer_id UUID NOT NULL REFERENCES customers(customer_id), order_data JSONB NOT NULL DEFAULT '{}', tags TEXT[] DEFAULT '{}', total_amount NUMERIC(12, 2) NOT NULL, created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(), updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW() );

Table Design

• Always define primary keys

• Use foreign keys with appropriate ON DELETE/UPDATE actions

• Add NOT NULL constraints where appropriate

• Use CHECK constraints for data validation

• Consider partitioning for large tables

  CREATE TABLE products ( product_id SERIAL PRIMARY KEY, sku VARCHAR(50) NOT NULL UNIQUE, name TEXT NOT NULL, price NUMERIC(10, 2) NOT NULL CHECK (price >= 0), status VARCHAR(20) NOT NULL DEFAULT 'active' CHECK (status IN ('active', 'inactive', 'discontinued')), metadata JSONB DEFAULT '{}' );

Partitioning

• Use declarative partitioning for large tables (millions of rows)

• Choose appropriate partition strategy: RANGE, LIST, or HASH

• Create indexes on partitioned tables after partitioning

  CREATE TABLE events ( event_id BIGSERIAL, event_type VARCHAR(50) NOT NULL, payload JSONB, created_at TIMESTAMPTZ NOT NULL ) PARTITION BY RANGE (created_at);

  CREATE TABLE events_2024_q1 PARTITION OF events FOR VALUES FROM ('2024-01-01') TO ('2024-04-01');

Indexing Strategies

Index Types

• Use B-tree indexes (default) for equality and range queries

• Use GIN indexes for JSONB, arrays, and full-text search

• Use GiST indexes for geometric data and range types

• Use BRIN indexes for large, naturally ordered data

• Consider partial indexes for filtered queries

  -- B-tree index for common lookups CREATE INDEX idx_orders_customer ON orders(customer_id);

  -- GIN index for JSONB queries CREATE INDEX idx_orders_data ON orders USING GIN (order_data);

  -- Partial index for active records only CREATE INDEX idx_active_products ON products(name) WHERE status = 'active';

  -- Covering index to avoid table lookup CREATE INDEX idx_orders_covering ON orders(customer_id) INCLUDE (order_date, total_amount);

Index Maintenance

• Regularly run ANALYZE to update statistics

• Use REINDEX for bloated indexes

• Monitor index usage with pg_stat_user_indexes

• Remove unused indexes to reduce write overhead

  -- Check index usage SELECT schemaname, relname, indexrelname, idx_scan, idx_tup_read FROM pg_stat_user_indexes ORDER BY idx_scan ASC;

Query Optimization

EXPLAIN ANALYZE

• Always analyze query plans for slow queries

• Look for sequential scans on large tables

• Identify missing indexes from query plans

• Watch for high row estimates vs actual rows

  EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT c.name, COUNT(o.order_id) FROM customers c LEFT JOIN orders o ON c.customer_id = o.customer_id WHERE c.created_at > '2024-01-01' GROUP BY c.customer_id, c.name;

Common Table Expressions (CTEs)

• Use CTEs for complex query organization

• Note: CTEs are optimization fences in older PostgreSQL versions

• Use MATERIALIZED/NOT MATERIALIZED hints in PostgreSQL 12+

  WITH recent_orders AS MATERIALIZED ( SELECT customer_id, COUNT(*) AS order_count, SUM(total) AS total_spent FROM orders WHERE order_date > CURRENT_DATE - INTERVAL '30 days' GROUP BY customer_id ) SELECT c.name, ro.order_count, ro.total_spent FROM customers c JOIN recent_orders ro ON c.customer_id = ro.customer_id WHERE ro.total_spent > 1000;

Window Functions

• Use window functions for analytics queries

• Leverage PARTITION BY and ORDER BY for complex calculations

  SELECT order_id, customer_id, total_amount, SUM(total_amount) OVER (PARTITION BY customer_id ORDER BY order_date) AS running_total, ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) AS order_rank FROM orders;

JSONB Best Practices

• Use JSONB over JSON for better performance and indexing

• Create GIN indexes for JSONB columns you query

• Use containment operators (@>, <@) for efficient queries

• Extract frequently queried fields to regular columns

  -- Efficient JSONB query with GIN index SELECT * FROM products WHERE metadata @> '{"category": "electronics"}';

  -- Extract specific fields SELECT product_id, metadata->>'brand' AS brand, (metadata->>'rating')::numeric AS rating FROM products WHERE metadata ? 'rating';

Connection Management

Connection Pooling

• Use PgBouncer or pgpool-II for connection pooling
• Set appropriate pool sizes based on workload
• Use transaction pooling mode for short-lived connections

Connection Settings

-- Recommended session settings
SET statement_timeout = '30s';
SET lock_timeout = '10s';
SET idle_in_transaction_session_timeout = '60s';

Transactions and Locking

• Use appropriate transaction isolation levels

• Keep transactions short to reduce lock contention

• Use advisory locks for application-level locking

• Monitor and resolve lock conflicts

  -- Use advisory locks for application coordination SELECT pg_advisory_lock(hashtext('resource_name')); -- Do work SELECT pg_advisory_unlock(hashtext('resource_name'));

  -- Check for blocking queries SELECT blocked_locks.pid AS blocked_pid, blocking_locks.pid AS blocking_pid, blocked_activity.query AS blocked_query FROM pg_catalog.pg_locks blocked_locks JOIN pg_catalog.pg_locks blocking_locks ON blocking_locks.locktype = blocked_locks.locktype AND blocking_locks.relation = blocked_locks.relation AND blocking_locks.pid != blocked_locks.pid JOIN pg_catalog.pg_stat_activity blocked_activity ON blocked_activity.pid = blocked_locks.pid;

Maintenance

Vacuum and Analyze

• Enable autovacuum and tune for your workload

• Run manual VACUUM ANALYZE after bulk operations

• Monitor table bloat

  -- Check table bloat SELECT schemaname, relname, n_live_tup, n_dead_tup, round(n_dead_tup * 100.0 / nullif(n_live_tup + n_dead_tup, 0), 2) AS dead_pct FROM pg_stat_user_tables WHERE n_dead_tup > 1000 ORDER BY n_dead_tup DESC;

Backup Strategies

• Use pg_dump for logical backups
• Use pg_basebackup for physical backups
• Implement point-in-time recovery (PITR) with WAL archiving
• Test backup restoration regularly

Security

• Use SSL/TLS for connections

• Implement row-level security (RLS) for multi-tenant applications

• Use roles and GRANT/REVOKE for access control

• Audit sensitive operations with pgAudit extension

  -- Enable row-level security ALTER TABLE documents ENABLE ROW LEVEL SECURITY;

  CREATE POLICY documents_tenant_policy ON documents FOR ALL USING (tenant_id = current_setting('app.tenant_id')::uuid);

  -- Grant minimal privileges GRANT SELECT, INSERT, UPDATE ON orders TO app_user; GRANT USAGE ON SEQUENCE orders_order_id_seq TO app_user;

Monitoring

• Monitor with pg_stat_statements extension

• Track slow queries and optimize regularly

• Set up alerts for replication lag, connection count, and disk usage

• Use pg_stat_activity to monitor active queries

  -- Enable pg_stat_statements CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

  -- Find slow queries SELECT query, calls, mean_exec_time, total_exec_time FROM pg_stat_statements ORDER BY mean_exec_time DESC LIMIT 10;

Weekly Installs

312

Repository

mindrally/skills

GitHub Stars

43

First Seen

Jan 25, 2026

Security Audits

Gen Agent Trust HubPassSocketPassSnykPass

Installed on

opencode269

gemini-cli261

codex254

github-copilot243

cursor218

kimi-cli205