Database Management

Postgresql Advanced This document provides comprehensive guidelines for postgresql advanced development and best practices. Advanced SQL Window Window functions for analytical queries Implement proper window functions for analytical queries Follow best practices for optimal results Common Common Table Expressions (CTEs) Implement proper common table expressions (ctes) Follow best practices for optimal results Recursive Recursive queries Implement proper recursive queries Follow best practices for optimal results JSONB JSONB operations and indexing Implement proper jsonb operations and indexing Follow best practices for optimal results Full-text Full-text search capabilities Implement proper full-text search capabilities Follow best practices for optimal results Performance Optimization Query Query plan analysis with EXPLAIN Implement proper query plan analysis with explain Follow best practices for optimal results Index Index usage and optimization Implement proper index usage and optimization Follow best practices for optimal results Table Table partitioning strategies Implement proper table partitioning strategies Follow best practices for optimal results Connection Connection pooling with PgBouncer Implement proper connection pooling with pgbouncer Follow best practices for optimal results Query Query optimization techniques Implement proper query optimization techniques Follow best practices for optimal results Data Types & Features JSONB JSONB for semi-structured data Implement proper jsonb for semi-structured data Follow best practices for optimal results Arrays Arrays for list data Implement proper arrays for list data Follow best practices for optimal results UUID UUID for unique identifiers Implement proper uuid for unique identifiers Follow best practices for optimal results Geometric Geometric types for spatial data Implement proper geometric types for spatial data Follow best practices for optimal results Custom Custom enumerated types Implement proper custom enumerated types Follow best practices for optimal results Backup & Recovery pg_dump pg_dump for logical backups Implement proper pg_dump for logical backups Follow best practices for optimal results Continuous Continuous archiving with WAL Implement proper continuous archiving with wal Follow best practices for optimal results Point-in-time Point-in-time recovery (PITR) Implement proper point-in-time recovery (pitr) Follow best practices for optimal results Streaming Streaming replication setup Implement proper streaming replication setup Follow best practices for optimal results Backup Backup verification strategies Implement proper backup verification strategies Follow best practices for optimal results High Availability Master-slave Master-slave replication Implement proper master-slave replication Follow best practices for optimal results Streaming Streaming replication Implement proper streaming replication Follow best practices for optimal results Logical Logical replication Implement proper logical replication Follow best practices for optimal results Connection Connection failover Implement proper connection failover Follow best practices for optimal results Load Load balancing strategies Implement proper load balancing strategies Follow best practices for optimal results Advanced Features Materialized Materialized views for performance Implement proper materialized views for performance Follow best practices for optimal results Foreign Foreign data wrappers (FDW) Implement proper foreign data wrappers (fdw) Follow best practices for optimal results Table Table inheritance Implement proper table inheritance Follow best practices for optimal results Exclusion Exclusion constraints Implement proper exclusion constraints Follow best practices for optimal results Extensions Extensions and custom types Implement proper extensions and custom types Follow best practices for optimal results Follow these comprehensive guidelines for successful postgresql advanced implementation.

MongoDB Database Design and Optimization Schema Design Patterns Document Structure Design Referenced vs Embedded Data Indexing Strategies Compound Index Design Index Performance Analysis Aggregation Pipeline Optimization Complex Aggregation Patterns Performance Optimization Techniques Data Modeling Patterns Polymorphic Pattern Bucket Pattern for Time Series Transaction Management Multi-Document Transactions Performance Monitoring and Optimization Database Profiling and Monitoring Query Optimization Strategies Data Validation and Schema Enforcement JSON Schema Validation Data Migration and Versioning Schema Migration Patterns Backup and Recovery Strategies Automated Backup Solutions Point-in-Time Recovery Security Best Practices Authentication and Authorization Implementation Checklist [ ] Design document schema based on access patterns [ ] Choose between embedding and referencing appropriately [ ] Create compound indexes for common query patterns [ ] Implement text search indexes for full-text search [ ] Set up geospatial indexes for location-based queries [ ] Use aggregation pipelines for complex data analysis [ ] Implement proper error handling and transactions [ ] Set up database validation rules [ ] Configure monitoring and profiling [ ] Implement automated backup strategy [ ] Set up proper authentication and authorization [ ] Plan for data migration and schema evolution [ ] Optimize queries based on explain plans [ ] Monitor collection and index statistics This comprehensive guide provides the foundation for building scalable, performant MongoDB applications with proper schema design, indexing strategies, and operational best practices.

Redis Caching Strategies and Implementation Redis Setup and Configuration Basic Redis Configuration Docker Compose Setup Cache Client Implementation TypeScript Redis Client Cache-Aside Pattern Implementation Repository with Caching Layer Write-Through and Write-Behind Patterns Write-Through Cache Implementation Write-Behind Cache with Queue Advanced Caching Patterns Multi-Level Cache Implementation Cache Warming Strategy Redis Data Structures for Caching Advanced Data Structure Usage Cache Monitoring and Metrics Performance Monitoring Testing Cache Implementation Comprehensive Test Suite Production Optimization Memory and Performance Tuning Deployment and Scaling Redis Cluster Configuration Implementation Checklist [ ] Set up Redis server with production configuration [ ] Implement cache service with proper error handling [ ] Choose appropriate caching patterns (cache-aside, write-through, etc.) [ ] Design cache key naming strategy [ ] Implement cache warming for critical data [ ] Set up multi-level caching if needed [ ] Use Redis data structures for advanced use cases [ ] Implement cache monitoring and metrics [ ] Write comprehensive tests for cache functionality [ ] Configure Redis cluster for high availability [ ] Set up cache invalidation strategies [ ] Monitor cache hit ratios and performance metrics This guide provides a comprehensive foundation for implementing Redis caching strategies that can significantly improve application performance and scalability while maintaining data consistency and reliability.

MySQL Database Development This document provides comprehensive guidelines for designing, optimizing, and managing MySQL databases for high-performance applications. Database Design Entity-Relationship Modeling Create clear ER diagrams for complex schemas Define relationships between entities properly Plan for future scalability and changes Normalization and Denormalization Apply normalization rules to reduce redundancy Use strategic denormalization for performance Balance between storage efficiency and query speed Schema Design Best Practices Use appropriate data types for columns Implement proper primary and foreign key constraints Plan table partitioning strategies for large datasets Indexing Strategies Index Types and Usage Implement B-tree indexes for range queries Use hash indexes for exact match lookups Create composite indexes for multi-column queries Index Design Best Practices Create covering indexes to avoid table lookups Use partial indexes for filtered queries Monitor index usage and remove unused indexes Replication and High Availability Replication Setup Configure master-slave replication for read scaling Implement master-master replication for write scaling Monitor replication lag and health Failover and Recovery Design automatic failover procedures Test disaster recovery scenarios regularly Implement proper backup and recovery strategies Security Best Practices Access Control Implement principle of least privilege for users Use strong password policies and rotation Configure SSL/TLS encryption for connections Auditing and Monitoring Enable audit logging for sensitive operations Monitor failed login attempts and suspicious activity Implement database firewall rules Scaling Strategies Horizontal Scaling Implement database sharding for large datasets Configure read replicas for read-heavy workloads Use connection pooling and load balancing Vertical Scaling Monitor resource usage and upgrade hardware Optimize memory allocation and CPU usage Plan for storage capacity growth Development Integration ORM Best Practices Configure connection pooling properly Implement efficient transaction management Use prepared statements to prevent SQL injection Error Handling Implement comprehensive error handling patterns Log database errors appropriately Plan for connection failure scenarios Build robust, high-performance MySQL databases following these comprehensive best practices.

Elasticsearch Search Engine Development Elasticsearch Setup and Configuration Basic Cluster Configuration Production Configuration Index Design and Mapping Document Mapping Strategy Search Client Implementation TypeScript Client Setup Advanced Search Queries Multi-Field Search with Boosting Auto-Complete and Suggestions Completion Suggester Implementation Performance Optimization Query Optimization Strategies Analytics and Monitoring Search Analytics Implementation Real-time Indexing Pipeline Event-Driven Indexing Testing Strategy Comprehensive Test Suite Production Deployment Docker and Kubernetes Deployment Implementation Checklist [ ] Set up Elasticsearch cluster with proper configuration [ ] Design index mappings for your data structure [ ] Implement search service with TypeScript client [ ] Create advanced search queries with filters and aggregations [ ] Build auto-complete and suggestion features [ ] Optimize query performance and indexing strategies [ ] Implement search analytics and monitoring [ ] Set up real-time indexing pipeline [ ] Write comprehensive tests for search functionality [ ] Deploy to production with monitoring and alerting [ ] Configure index lifecycle management [ ] Implement security and access controls This guide provides a production-ready foundation for building sophisticated search engines with Elasticsearch, covering everything from basic setup to advanced features and deployment strategies.