Database

Redis is powerful for caching. Here are effective caching strategies. Cache-Aside Pattern async function getUser(id) { // Check cache let user = await redis.get(`user:${id}`); if (user) { return JSON.parse(user); } // Cache miss - fetch from DB user = await db.query('SELECT * FROM users WHERE id = ?', [id]); // Store in cache await redis.setex(`user:${id}`, 3600, JSON.stringify(user)); return user; } Write-Through Pattern async function updateUser(id, data) { // Update database const user = await db.update('users', id, data); // Update cache await redis.setex(`user:${id}`, 3600, JSON.stringify(user)); return user; } Cache Invalidation async function deleteUser(id) { // Delete from database await db.delete('users', id); // Invalidate cache await redis.del(`user:${id}`); } Best Practices Set appropriate TTL Handle cache misses Invalidate properly Monitor cache hit rate Use consistent key patterns Conclusion Implement effective Redis caching strategies! 🔴

Optimizing MongoDB queries is essential for performance. Here’s how. Indexing Create Indexes // Single field index db.users.createIndex({ email: 1 }); // Compound index db.users.createIndex({ status: 1, createdAt: -1 }); // Text index db.posts.createIndex({ title: "text", content: "text" }); Explain Queries db.users.find({ email: "[email protected]" }).explain("executionStats"); Query Optimization Use Projection // Bad: Fetches all fields db.users.find({ status: "active" }); // Good: Only needed fields db.users.find( { status: "active" }, { name: 1, email: 1, _id: 0 } ); Limit Results db.users.find({ status: "active" }) .limit(10) .sort({ createdAt: -1 }); Best Practices Create appropriate indexes Use projection Limit result sets Avoid $regex without index Monitor slow queries Conclusion Optimize MongoDB for better performance! 🍃

Elasticsearch is powerful for search. Here’s how to get started. Basic Operations Create Index await client.indices.create({ index: 'users', body: { mappings: { properties: { name: { type: 'text' }, email: { type: 'keyword' }, age: { type: 'integer' } } } } }); Index Document await client.index({ index: 'users', id: '1', body: { name: 'John Doe', email: '[email protected]', age: 30 } }); Search const result = await client.search({ index: 'users', body: { query: { match: { name: 'John' } } } }); Best Practices Design mappings carefully Use appropriate analyzers Optimize queries Monitor cluster health Backup regularly Conclusion Master Elasticsearch for powerful search! 🔍

PostgreSQL performance tuning requires understanding configuration and queries. Here’s a guide. Configuration Tuning postgresql.conf # Memory settings shared_buffers = 256MB effective_cache_size = 1GB work_mem = 16MB # Connection settings max_connections = 100 # Query planner random_page_cost = 1.1 Query Optimization Use EXPLAIN ANALYZE EXPLAIN ANALYZE SELECT * FROM users WHERE email = '[email protected]'; Indexing -- B-tree index CREATE INDEX idx_user_email ON users(email); -- Partial index CREATE INDEX idx_active_users ON users(email) WHERE status = 'active'; -- Composite index CREATE INDEX idx_user_status_created ON users(status, created_at); Best Practices Analyze query plans Create appropriate indexes Use connection pooling Monitor slow queries Vacuum regularly Conclusion Tune PostgreSQL for optimal performance! 🐘

Using SQLAlchemy with async Python requires understanding async patterns. Here’s how. Setup from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession from sqlalchemy.orm import sessionmaker engine = create_async_engine("postgresql+asyncpg://user:pass@localhost/db") AsyncSessionLocal = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False) Async Models from sqlalchemy.ext.declarative import declarative_base from sqlalchemy import Column, Integer, String Base = declarative_base() class User(Base): __tablename__ = "users" id = Column(Integer, primary_key=True) name = Column(String) Async Operations async def create_user(name: str): async with AsyncSessionLocal() as session: user = User(name=name) session.add(user) await session.commit() return user async def get_user(user_id: int): async with AsyncSessionLocal() as session: result = await session.get(User, user_id) return result Best Practices Use async context managers Commit transactions explicitly Handle exceptions properly Use connection pooling Close sessions correctly Conclusion Build efficient async database applications with SQLAlchemy! 🐍