PostgreSQL Performance Tuning for High-Traffic Applications

Why PostgreSQL?

PostgreSQL is the world's most advanced open-source relational database, powering Odoo, ERPNext, and thousands of enterprise applications. But out-of-the-box configuration is not optimized for high-traffic workloads.

Indexing Strategy

Indexes are the single most impactful performance optimization. Use EXPLAIN ANALYZE to identify slow queries, then add appropriate indexes:

-- B-tree index for equality and range queries
CREATE INDEX idx_orders_customer ON orders(customer_id);

-- Partial index for filtered queries
CREATE INDEX idx_active_products ON products(status) WHERE status = 'active';

-- Composite index for multi-column queries
CREATE INDEX idx_invoice_date_status ON invoices(invoice_date, status);

Connection Pooling

PostgreSQL forks a new process for each connection. Under high traffic, this exhausts memory. Use PgBouncer or pgpool-II to pool connections. Recommended: max_connections = (CPU cores * 2) + effective_spindle_count.

Configuration Tuning

• shared_buffers: 25% of system RAM
• effective_cache_size: 75% of system RAM
• work_mem: 256MB (per operation, not per connection)
• max_parallel_workers_per_gather: equal to CPU cores

Monitoring

Use pg_stat_statements to identify slow queries. Monitor pg_stat_activity for connection issues. Set up Prometheus + Grafana for real-time dashboards.