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This article explains how Java developers can replace thousands of individual UPDATE statements with a single PostgreSQL stored procedure call, covering the motivation, procedure creation, Java invocation, scheduling with shell scripts, performance benchmarks, and common pitfalls.
This article introduces Supabase, an open‑source Firebase alternative built on PostgreSQL that offers RESTful and GraphQL APIs, real‑time data sync, authentication, and serverless functions, and provides step‑by‑step guidance for cloud‑hosted or local deployment to accelerate backend development.
This article presents a real‑world case study of a high‑traffic backend API that originally took 30 seconds to process over two million records, detailing problem diagnosis, SQL and Java code analysis, and a series of optimizations—including SQL rewrites, database‑side aggregation, and Caffeine caching—that ultimately cut the response time to under one second.
This article provides an extensive overview of widely used database management tools across various platforms—including DBeaver, Navicat, PL/SQL Developer, Toad for Oracle, SQLyog, MySQL Workbench, HeidiSQL, Percona Toolkit, pgAdmin, SQLite Expert, and SSMS—detailing their supported databases, core features, licensing, download links, and related learning resources.
This tutorial explains why DBAs need security hardening and log analysis, shows how to configure minimal‑privilege roles and precise permissions in PostgreSQL, demonstrates how to detect and revoke redundant privileges, and provides a step‑by‑step guide to installing and using pgBadger for log analysis and automated reporting.
The benchmark comparing MySQL 9.0 and PostgreSQL 17.0 shows PostgreSQL consistently achieving lower insertion latency, roughly double the throughput (≈19 k QPS vs 10 k QPS), using less CPU, memory and disk I/O, while both hit an 80‑connection pool limit and PostgreSQL maintains stable read latency as MySQL’s performance degrades beyond ~5.5 k QPS.
This guide explains how to diagnose and fix a PostgreSQL instance that fails to start after a power outage, covering log inspection, missing socket files, PID checks, checkpoint corruption detection, and recovery using pg_resetwal.
Choosing the proper MySQL or PostgreSQL date/time column—avoiding string types, understanding DATETIME’s literal storage versus TIMESTAMP’s automatic UTC conversion, considering PostgreSQL’s TIMESTAMP WITH/WITHOUT TIME ZONE equivalents, and weighing numeric Unix timestamps for speed—ensures correct time‑zone handling, storage efficiency, and future‑proof range.
The article examines three modern, cloud‑native and open‑source methods for deploying PostgreSQL—using the CloudNativePG operator on Kubernetes, leveraging Korifi’s self‑service platform, and adopting Neon’s compute‑storage separation—highlighting trends toward cloud‑native infrastructure, self‑service, and open‑source SaaS alternatives.
This article compares Oracle, PostgreSQL, and MySQL across core features, typical use cases, transaction support, storage engines, licensing, provides simplified installation steps, demonstrates basic SQL operations such as creating tables, inserting and querying data, and highlights key differences like auto‑increment handling and string‑matching functions.
The article analyzes recent industry data and expert observations showing PostgreSQL surpassing MySQL in cloud instance counts, CPU usage, and ecosystem support, especially in vector‑database and serverless contexts, while highlighting MySQL's strategic shortcomings and predicting PostgreSQL's dominance in the coming years.
This article introduces ten common Python database interaction patterns—from basic CRUD operations and table creation to advanced transaction handling, batch inserts, and stored procedures—culminating in a complete user‑registration system example that demonstrates how to combine these techniques effectively.
The article compares MySQL and PostgreSQL multi‑table join capabilities, explains why MySQL’s nested‑loop joins can be less efficient for complex queries, and discusses how decomposing joins into separate single‑table queries or moving logic to the service layer can improve performance, scalability, and caching.
This article explains how to improve PostgreSQL IN‑query performance in Spring Boot applications by splitting large IN parameter lists into smaller batches, executing them concurrently with a custom AOP annotation, and merging the results, providing a reusable annotation‑driven solution for high‑throughput backend services.
This article presents a real‑world case study of a high‑concurrency data‑processing interface whose response time was reduced from 30 seconds to under one second by diagnosing SQL bottlenecks, applying PostgreSQL array aggregation, moving logic to the database, and introducing Caffeine caching, with detailed code examples and performance analysis.
This article explains how to improve performance of massive IN‑list queries in PostgreSQL by splitting the parameter list, executing the sub‑queries concurrently with a custom Spring AOP annotation, and merging the results using a configurable thread pool and return‑handling strategy.
This article explains how to improve performance of massive IN‑list queries in PostgreSQL by splitting the list, executing sub‑queries in parallel using a custom Spring AOP annotation, and merging the results with a configurable handler, providing a reusable solution for Java backend services.
Learn how to deploy a highly available Nacos service on Kubernetes using PostgreSQL as the backend, covering prerequisites, database initialization, configuration, Helm‑free manifests, driver installation, and verification steps to build a reliable micro‑service platform.
This guide explains why a PostgreSQL connection attempt fails with “FATAL: password authentication failed for user ‘postgres’”, outlines common causes such as wrong passwords and misconfigured postgresql.conf or pg_hba.conf, and provides step‑by‑step solutions including password reset, config correction, trust authentication and environment rebuild.
DBOS, a Database‑Oriented Operating System proposed by Matei Zaharia and Michael Stonebrake, builds the OS atop a distributed, ACID‑compliant database, storing all system and application state in tables, which simplifies scaling, ensures strong consistency, improves debugging, and reduces attack surface for cloud‑native workloads.