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;