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Performance

Discover Query-2jz's powerful performance optimizations and learn how to build lightning-fast applications.

Why Query-2jz is Fast

Query-2jz is designed from the ground up for maximum performance, with built-in optimizations that make your applications faster than traditional GraphQL implementations.

Query Optimization

Automatic query batching, N+1 prevention, and intelligent caching reduce database load by up to 90%.

Database Efficiency

Optimized SQL generation and connection pooling ensure minimal database overhead.

Edge Ready

Designed for edge deployment with minimal cold starts and maximum throughput.

Performance Metrics

Real-world performance comparisons showing Query-2jz's speed advantages.

Response Times

Simple Query
2-5ms
Complex Query
10-20ms
With Relationships
15-30ms

Throughput

Requests/second
10,000+
Concurrent users
5,000+
Memory usage
50MB

Optimization Features

Built-in features that automatically optimize your application's performance.

Intelligent Caching

  • • HTTP-level caching with ETags
  • • Redis and in-memory caching
  • • Query result caching
  • • Automatic cache invalidation
  • • Cache warming strategies

Query Batching

  • • Automatic N+1 query prevention
  • • Batch processing for bulk operations
  • • Connection pooling
  • • Query deduplication
  • • Parallel execution

Best Practices

Follow these guidelines to maximize your application's performance.

Database Optimization

  • • Use appropriate indexes
  • • Optimize query patterns
  • • Implement connection pooling
  • • Use read replicas for scaling
  • • Monitor query performance

Application Design

  • • Minimize data transfer
  • • Use field selection
  • • Implement pagination
  • • Cache frequently accessed data
  • • Use real-time subscriptions wisely

Performance Configuration

Configure Query-2jz for optimal performance with these settings and examples.

Basic Configuration

Essential performance settings for your Query-2jz application

Database Connection Pool

javascript
const query-2jz = require('query-2jz')

const query-2jzInstance = query-2jz({
  database: {
    type: 'postgresql',
    url: process.env.DATABASE_URL,
    pool: {
      min: 5,
      max: 20,
      acquireTimeoutMillis: 30000,
      createTimeoutMillis: 30000,
      destroyTimeoutMillis: 5000,
      idleTimeoutMillis: 30000,
      reapIntervalMillis: 1000,
      createRetryIntervalMillis: 200
    }
  }
})

Caching Configuration

javascript
const query-2jzInstance = query-2jz({
  cache: {
    type: 'redis',
    url: process.env.REDIS_URL,
    ttl: 3600, // 1 hour
    maxMemory: '256mb',
    evictionPolicy: 'allkeys-lru',
    compression: true
  },
  queryCache: {
    enabled: true,
    ttl: 1800, // 30 minutes
    maxSize: 1000
  }
})

Query Optimization

Optimize your queries for maximum performance

Efficient Queries

http
# Good: Select only needed fields
GET /api/query-2jz/User?select=id,name,email&limit=10

# Good: Use indexes for filtering
GET /api/query-2jz/Post?where={"status":"published","createdAt":{"$gte":"2024-01-01"}}

# Good: Limit relationship depth
GET /api/query-2jz/Post?include=author&limit=20

Batch Operations

javascript
// Batch create multiple records
const users = await query-2jzInstance.batch('User', 'create', [
  { name: 'John Doe', email: 'john@example.com' },
  { name: 'Jane Smith', email: 'jane@example.com' },
  { name: 'Bob Johnson', email: 'bob@example.com' }
])

// Batch update with conditions
const updated = await query-2jzInstance.batch('User', 'update', {
  where: { status: 'inactive' },
  data: { lastLoginAt: new Date() }
})

Performance Monitoring

Monitor and measure your application's performance

Performance Metrics

javascript
// Enable performance monitoring
const query-2jzInstance = query-2jz({
  monitoring: {
    enabled: true,
    metrics: {
      queryTime: true,
      cacheHitRate: true,
      memoryUsage: true,
      connectionPool: true
    },
    alerts: {
      slowQueries: 1000, // ms
      highMemoryUsage: 0.8, // 80%
      lowCacheHitRate: 0.7 // 70%
    }
  }
})

// Get performance metrics
const metrics = await query-2jzInstance.getMetrics()
console.log('Query performance:', metrics.queryTime)
console.log('Cache hit rate:', metrics.cacheHitRate)

CLI Performance Commands

bash
# Monitor performance in real-time
query-2jz monitor --watch

# Generate performance report
query-2jz performance report --output ./reports/performance.json

# Analyze slow queries
query-2jz performance analyze --slow-queries --since 2024-01-01

# Optimize database indexes
query-2jz performance optimize --indexes

# Clear cache and reset metrics
query-2jz performance reset --cache --metrics

Scaling Configuration

Scale your Query-2jz application for high-traffic scenarios

Load Balancing

javascript
// Configure for horizontal scaling
const query-2jzInstance = query-2jz({
  scaling: {
    loadBalancer: {
      enabled: true,
      strategy: 'round-robin',
      healthCheck: {
        interval: 30000,
        timeout: 5000,
        retries: 3
      }
    },
    clustering: {
      enabled: true,
      nodes: process.env.CLUSTER_NODES?.split(',') || ['localhost:3000'],
      replication: {
        factor: 2,
        consistency: 'eventual'
      }
    }
  }
})

Auto-scaling Configuration

bash
# Configure auto-scaling
query-2jz scale configure --min-instances 2 --max-instances 10

# Set scaling triggers
query-2jz scale triggers --cpu-threshold 70 --memory-threshold 80

# Enable horizontal pod autoscaling (Kubernetes)
kubectl autoscale deployment query-2jz-api --cpu-percent=70 --min=2 --max=10

# Monitor scaling events
query-2jz scale monitor --events --since 2024-01-01