Database

PostgreSQL’s work_mem parameter is one of the most impactful yet misunderstood configuration settings for database performance. This post explores how adjusting work_mem can dramatically improve query execution times, especially for operations involving sorting, hashing, and joins. Understanding work_mem work_mem specifies the amount of memory PostgreSQL can use for internal sort operations and hash tables before writing to temporary disk files. The default value is 4MB, which is conservative to ensure PostgreSQL runs on smaller machines. ...

Elasticsearch is a powerful search and analytics engine, but optimizing it for production requires understanding indexing strategies, query patterns, and cluster configuration. This guide covers essential optimization techniques. Cluster architecture Node roles Configure nodes with specific roles: # Master node node.roles: [master] # Data node node.roles: [data] # Ingest node node.roles: [ingest] # Coordinating node (default) node.roles: [] # No specific role Shard strategy Primary shards: Set at index creation (cannot be changed) ...

MongoDB performance optimization requires a systematic approach to identify bottlenecks, analyze query patterns, and implement effective indexing strategies. This guide covers profiling techniques, index optimization, and load testing methodologies. Understanding MongoDB performance MongoDB performance depends on several factors: Query patterns: How queries are structured and what operations they perform Index usage: Whether queries can leverage indexes effectively Data volume: Size of collections and documents Hardware resources: CPU, memory, and disk I/O capacity Connection pooling: How applications manage database connections Profiling MongoDB queries Enable profiling MongoDB’s profiler collects detailed information about query execution: ...