Database Performance Optimization

Automatic query analysis, execution plan visualization, and intelligent recommendations to keep your database running at peak efficiency.

performance-analyzer.sql
EXPLAIN ANALYZE
SELECT o.id, o.total, c.name FROM orders o
JOIN customers c ON o.customer_id = c.id
WHERE o.created_at > '2026-01-01'
ORDER BY o.total DESC LIMIT 100;
Execution Plan:
↳ Limit (cost=245.32..245.57 rows=100)
↳ Sort (cost=245.32..245.57 rows=850)
↳ Hash Join (cost=85.50..175.00 rows=850)
→ Seq Scan on orders o (cost=0.00..45.00 rows=1000)
Filter: (created_at > '2026-01-01')
→ Hash (cost=25.00..25.00 rows=500)
→ Seq Scan on customers c
⚠ Recommendations:
1. Create index: CREATE INDEX idx_orders_created ON orders(created_at)
Estimated improvement: 45% faster
2. Consider partial index for recent orders
Estimated improvement: 60% faster
✓ This query is using efficient join strategy

🔍 Query Analysis

Detailed execution plans with cost analysis. Identify slow scans, missing indexes, and suboptimal joins.

  • ✓ Automatic slow query detection
  • ✓ Plan visualization
  • ✓ Historical comparison

💡 Recommendations

Machine learning-powered recommendations for indexes, query rewrites, and schema optimization.

  • ✓ Impact estimation
  • ✓ Safe to apply
  • ✓ One-click optimization

📈 Benchmarking

Compare query performance before and after optimization. Measure the real impact of your changes.

  • ✓ A/B testing
  • ✓ Performance metrics
  • ✓ Regression detection

Performance Insights & Tuning

Index Optimization

DBForge analyzes query patterns and automatically recommends indexes that will have the most impact on performance.

Recommended Indexes:
idx_orders_customer_date
Estimated 45% improvement
idx_transactions_status_created
Estimated 32% improvement
Unused Indexes:
idx_old_customer_lookup
Not used in 30 days
idx_archive_status
Removing saves 2.3GB

Query Timeline Analysis

Visualize query execution over time. Identify patterns, spikes, and performance degradation.

Last 24 Hours Performance
00:00-02:00 ▓▓▓░░░░░░ 35ms avg
02:00-04:00 ▓░░░░░░░░ 12ms avg
04:00-06:00 ▓░░░░░░░░ 9ms avg
06:00-08:00 ▓▓▓▓▓░░░░ 78ms avg
08:00-10:00 ▓▓▓▓▓▓░░░ 95ms avg
10:00-12:00 ▓▓▓▓░░░░░ 48ms avg
12:00-14:00 ▓▓░░░░░░░ 28ms avg
14:00-16:00 ▓░░░░░░░░ 15ms avg

Schema Optimization

Get recommendations for schema changes that can improve query performance and reduce storage.

Columnstore Index

Analytical queries 10x faster

Current: Row-based storage
Recommended: Columnstore index on analytics table
Size reduction: 65%
Partitioning

Faster queries on large tables

Current: Single partition
Recommended: Date-based partition
Query improvement: 40%