This article showcases a collection of impressive SQL queries—including a PostgreSQL Tetris implemented with a recursive CTE, window‑function session analysis, a ClickHouse real‑time funnel, dynamic WHERE clause generation, and a recursive employee hierarchy—while discussing performance tips and engine choices.
The article explains why increasing PostgreSQL's work_mem does not guarantee per‑query memory limits, how multiple sort/hash nodes, parallel workers and long‑lived memory contexts can cause OOM even on a 2 TB server, and offers concrete diagnostics and mitigation strategies for DBAs and developers.
The article questions whether dedicated vector databases are truly needed for AI applications, examining market hype, the rapid emergence of many vector‑DB products, real‑world examples like PostgreSQL pgvector and major vendor integrations, and the hidden costs of data fragmentation and operational complexity.
An AI‑driven security tool discovered high‑severity, remote‑code‑execution flaws in PostgreSQL's pgcrypto extension and MariaDB's JSON schema validation, both dating back over two decades, prompting immediate patch releases and offering mitigation steps for unpatched deployments.
The article compares PostgreSQL and MySQL, highlighting PostgreSQL's richer data types, extensible ecosystem, advanced replication and monitoring features, while exposing MySQL's limitations in data modeling, sequence support, tooling, and replication, and concludes that the best choice depends on specific workload requirements.
The php.internals vote on April 4 approved moving PHP 9.0 to the permissive 3‑clause BSD license, replacing the dual PHP v3.01 and Zend Engine licenses, and the article explains the historical reasons, legal benefits, comparisons with other BSD variants, PostgreSQL’s approach, and broader open‑source licensing trends.
The article argues that relying on many specialized databases creates operational complexity, higher costs, and maintenance overhead, while PostgreSQL’s extensible ecosystem—offering full‑text search, vector, time‑series, JSONB, and more—delivers comparable or superior algorithms, proven performance, and a simpler, more reliable stack for the vast majority of use cases, especially in AI applications.
The article compares PostgreSQL and MySQL across data types, native sequences, extensions, monitoring tools, replication mechanisms, licensing, community governance, and MVCC implementation, showing why many Chinese tech giants favor PostgreSQL for complex, high‑consistency workloads while acknowledging MySQL’s strengths in simple web scenarios.
PostgreSQL’s extensible architecture lets it evolve from a relational DB into a true multi‑model system supporting graphs, vectors, full‑text, time‑series, GIS and key‑value data, with detailed architecture explanations, practical code demos, cross‑model queries, extension selection, and production‑grade best‑practice tips.
This article examines how PostgreSQL can take over Redis' roles—caching, pub/sub, and job queues—by leveraging unlogged tables, LISTEN/NOTIFY, and SKIP LOCKED, presenting cost savings, benchmark results, migration steps, and code examples for a practical backend replacement.
TimescaleDB 2.26.2 focuses on fixing high‑impact bugs—continuous aggregates errors, compression task crashes, and lock‑related deadlocks—while improving memory stability and PostgreSQL compatibility, and the article provides detailed upgrade instructions and best‑practice recommendations.
This article explains PostgreSQL's native full‑text search, its core concepts of tsvector and tsquery, demonstrates how to use built‑in functions and operators, compares built‑in, zhparser, and pg_search extensions for Chinese tokenization, and provides best‑practice tips for indexing, triggers, and performance optimization.
The article analyzes why many Chinese cloud providers and enterprises prefer PostgreSQL to MySQL, detailing PostgreSQL's richer data types, native sequence support, extensible ecosystem, advanced monitoring, robust replication, open licensing, and MVCC implementation, while acknowledging MySQL's remaining advantages in specific scenarios.
This article compares PostgreSQL and SQL Server data access methods—including sequential scans, index scans, bitmap heap scans, index‑only scans, and parallel query execution—highlighting PostgreSQL's lack of clustered indexes and the performance implications of each approach.
This comprehensive guide explores PostgreSQL 17's lock mechanisms, covering lock classifications, table‑ and row‑level lock behavior, MVCC interaction, common pitfalls such as deadlocks and lock contention, and provides practical SQL queries, Bash monitoring scripts, advisory‑lock techniques, and best‑practice recommendations for performance tuning and reliable production deployment.
Amid China's push for independent, cloud‑native databases, leading firms like Tencent, Alibaba, Huawei and others have built PostgreSQL‑based solutions, and this article analyzes why PostgreSQL’s richer data types, true sequence objects, extensible ecosystem, advanced replication and licensing advantages make it a preferred choice over MySQL.
In 2026 the database ecosystem faces fierce competition between MySQL and PostgreSQL, while AI emerges as a new driver prompting open‑source projects like AliSQL to release DuckDB, vector engines and intelligent CLI, reshaping how relational databases serve both transactional and analytical workloads.
This article explains how combining Go, PostgreSQL, and sqlc creates a Zero‑ORM architecture that restores SQL to the center of high‑performance, highly controllable, and maintainable backend services, covering design principles, layer responsibilities, schema and query patterns, connection‑pool tuning, transaction handling, observability, and practical best‑practice checklists.
The article explains how Gemini CLI’s shift from traditional Tools to progressive Agent Skills streamlines Cloud SQL for PostgreSQL extensions, reducing context overload, enabling on‑demand skill loading, zero‑manual installation, and cross‑platform execution, and provides step‑by‑step commands for exploring and using these new capabilities.
The article examines the sharp decline in MySQL’s commit activity since its 2006‑2007 peak, compares recent DB‑Engines rankings that show PostgreSQL overtaking MySQL, and attributes the downturn to Oracle’s management practices, technical setbacks, reduced open‑source community engagement, and a shift toward proprietary alternatives.
This guide explains how to set up Prometheus monitoring for PostgreSQL using the open‑source postgres_exporter, covering both single‑node Docker installation and multi‑node configuration with custom authentication files and Prometheus scrape settings.
This guide explains what PostgreSQL execution plans are, how they are generated, and how to interpret them using EXPLAIN and EXPLAIN ANALYZE, then demonstrates three real‑world case studies that show step‑by‑step optimizations with indexes, configuration tweaks, and query rewrites to dramatically improve query speed.
This comprehensive guide walks you through PostgreSQL 17 deployment, explains its multi‑process architecture and MVCC model, details environment requirements, shows essential configuration parameters, provides step‑by‑step backup and PITR procedures, demonstrates streaming replication setup, and shares best‑practice tuning, security, and monitoring tips for reliable production use.
A concise roundup of major AI developments on March 2, 2026, covering Palantir's stock surge linked to Anthropic tech in a US airstrike, OpenAI's controversial DoD agreement, breakthroughs in large‑model optimization, PostgreSQL scaling, competitive wins, new recommendation systems, open‑source model releases, and emerging research from top universities.
The article analyzes why many leading Chinese tech firms adopt PostgreSQL despite MySQL’s popularity, detailing PostgreSQL’s richer data types, native sequence support, extensible ecosystem, advanced monitoring tools, robust replication, open‑source licensing, and MVCC implementation, while also acknowledging MySQL’s strengths in simple deployment and read‑heavy workloads.
This guide explains the advantages of using PDO instead of mysqli for PHP database connections, walks through MySQL and PostgreSQL setup with detailed code examples, recommended configuration options, and a checklist for troubleshooting common connection errors.
This guide introduces a collection of PostgreSQL SKILL scripts for automated health checks and operational analysis, explains the repository layout, shows how to run individual or full daily checks, lists all available skills, and provides a sample report with actionable recommendations.
The article examines why major Chinese cloud and technology providers are building distributed, cloud‑native or HTAP databases on PostgreSQL instead of MySQL, detailing differences in data types, sequences, extensions, monitoring, replication, licensing, and MVCC implementation.
Amid rising demand for open‑source, self‑controlled databases in China, major firms such as Tencent, Alibaba, and Huawei have built PostgreSQL‑based distributed, cloud‑native solutions, citing PostgreSQL’s richer data types, native sequence support, extensible ecosystem, advanced monitoring, robust replication, and true open‑source licensing as decisive advantages over MySQL.
In under a month the author migrated more than 100 heterogeneous tables from MySQL and MongoDB to PostgreSQL across isolated networks by automating Navicat's import/export logic, streaming data, handling special characters, configuring flexible sync strategies, and using OSS as a bridge to avoid OOM and lock‑contention.
The article reveals seven common PostgreSQL architectural oversights—such as neglecting vacuum, misusing UUID primary keys, treating the database as a queue, missing indexes, over‑relying on ORMs, ignoring write‑side scaling, and failing to partition large tables—that silently degrade performance and reliability, and provides concrete fixes and best‑practice configurations.
OpenAI’s engineering team expanded a single‑primary PostgreSQL cluster with nearly 50 read‑only replicas, migrated write‑heavy workloads to Azure Cosmos DB, and applied extensive optimizations to reliably serve the global traffic of ChatGPT and the OpenAI API for 800 million users at multi‑million queries per second.
This article compares PostgreSQL and MySQL, highlighting PostgreSQL's richer data types, native sequences, extensible ecosystem, advanced monitoring, robust replication, open licensing, and MVCC implementation, while also acknowledging MySQL's strengths in simplicity and read‑heavy web workloads.
OpenAI runs a single primary PostgreSQL with about 50 replicas to serve roughly 800 million ChatGPT users, employing PgBouncer connection pooling, cache‑lock mechanisms, query and schema optimizations, workload isolation, multi‑layer throttling, and cascade replication, while acknowledging the architecture’s limits and the complexity of full sharding.
The article debunks OpenAI's sensational claim of handling 800 million ChatGPT users with a single PostgreSQL instance, revealing a pragmatic hybrid architecture that combines many read replicas, Azure CosmosDB for write‑heavy workloads, and top‑tier hardware, while highlighting cost and complexity considerations.
The article compares PostgreSQL and MySQL, detailing PostgreSQL’s richer data types, true sequence support, extensible ecosystem, advanced monitoring and replication features, while also acknowledging MySQL’s simplicity and strong points, to help readers decide which database fits their workload best.
The article examines why major Chinese cloud providers and enterprises are building PostgreSQL‑based distributed, cloud‑native databases instead of MySQL, detailing PostgreSQL's richer data types, native sequence support, extensible ecosystem, advanced replication, licensing advantages, and MVCC implementation, while also noting MySQL's remaining strengths.
This guide enumerates frequent misconceptions in SQL performance—from over‑indexing and SELECT * misuse to improper transaction handling and outdated monitoring practices—explains why they hurt efficiency, and provides concrete, version‑aware solutions to optimize queries, schema design, and database operations.
The article compares PostgreSQL and MySQL, highlighting PostgreSQL's richer data types, true sequence support, powerful extensions, built‑in monitoring, advanced replication, open‑source licensing, and MVCC implementation, while acknowledging MySQL's strengths in quick deployment and read‑heavy workloads.
This guide explains how Apache AGE extends PostgreSQL with OpenCypher‑compatible graph capabilities, covering architecture, installation, storage schema, Cypher‑SQL integration, common graph operations, and a LangChain example that turns natural‑language questions into executable graph queries.
The article argues that a single PostgreSQL instance can handle caching, queuing, full‑text search, and real‑time notifications, eliminating the need for separate services like Redis, RabbitMQ, and Elasticsearch, while reducing cost and complexity.
This article compiles a detailed comparison of PostgreSQL and MySQL, highlighting PostgreSQL's lack of text‑size limits, better NULL handling, native array and JSON support, built‑in optimistic locking, superior GIS types, MVCC, flexible indexing, robust replication, and overall stability, while also noting the few areas where MySQL still holds an edge.
This article compares the execution‑plan generation, caching, and query‑performance characteristics of Oracle, MySQL, and PostgreSQL, explains how to view plans in each system, and provides practical tips for DBAs to interpret and optimize them effectively.
This guide walks through switching a SpringBoot + MyBatisPlus project from MySQL to PostgreSQL, covering driver setup, JDBC changes, numerous SQL syntax differences, type conversion issues, transaction handling, and provides helper scripts for bulk schema adjustments.
This comprehensive guide explains PostgreSQL backup and recovery techniques—including logical and physical backups, point‑in‑time recovery, automation scripts, security measures, and production‑grade best practices—to ensure data availability, integrity, and compliance.
PostgreSQL offers four transaction isolation levels—READ UNCOMMITTED, READ COMMITTED, REPEATABLE READ, and SERIALIZABLE—each preventing specific concurrency anomalies like dirty reads, non‑repeatable reads, and phantom reads, and the article explains their behavior, configuration commands, practical usage, performance trade‑offs, and production best practices.
This article explains why modern enterprises should avoid single‑database solutions, compares PostgreSQL and MongoDB across core philosophy, technical capabilities, ecosystem extensions, and cost, and provides a decision framework, real‑world case studies, and a hybrid architecture blueprint for scalable, low‑risk systems.
SQLAlchemy 2.0.45 resolves a race‑condition in greenlet‑based connection pools that caused intermittent 500 errors under load, improves cross‑database parameter handling and SQLite reflection, and includes performance benchmarks and a safe upgrade guide for Python backend developers.
An in‑depth enterprise guide explains why backup and replication are critical for PostgreSQL, compares physical, logical, and logical replication methods, provides step‑by‑step command examples, outlines high‑availability architectures, automation scripts, disaster‑recovery procedures, monitoring queries, and common pitfalls to ensure robust data protection.
VectorChord‑BM25 is a PostgreSQL extension that adds native BM25 ranking and tokenization, delivering up to three‑fold query‑per‑second improvements over ElasticSearch while maintaining comparable relevance scores, and includes detailed installation, usage examples, and performance analysis.
This article examines Dify’s production‑scale bottlenecks caused by heavy PostgreSQL logging, explains why a cloud‑native log service (SLS) better matches the append‑only, high‑throughput nature of workflow logs, and provides a step‑by‑step migration guide that dramatically reduces database pressure, storage cost, and unlocks advanced analytics.
The article examines why leading Chinese tech firms are increasingly adopting PostgreSQL instead of MySQL, detailing PostgreSQL‑based products, comparing data‑type support, sequence handling, extensions, monitoring tools, replication mechanisms, licensing, community openness, and MVCC implementation, while also outlining MySQL's limitations.
The article recounts how a PostgreSQL instance on a modest 2‑CPU, 4 GB VM handling 1.2 billion rows was dramatically accelerated by adding BRIN indexes, scheduling maintenance with pg_cron, applying query folding and tuning memory and parallel settings, achieving sub‑second query times without additional hardware.
This comprehensive guide explains PostgreSQL's Write-Ahead Logging (WAL) fundamentals, its role in durability, crash recovery, PITR and streaming replication, details the checkpoint mechanism, essential monitoring queries, production‑grade configuration recommendations, backup and recovery procedures, and practical DBA checklists for reliable operations.
The article examines how PostgreSQL’s latest pgvector 0.8.0 release adds iterative index scans and smart query planning, enabling fully free vector search within an existing relational database, compares performance, cost, and architecture against dedicated vector databases like Pinecone, and outlines migration steps and best‑practice guidelines.
This article explains how the River library leverages PostgreSQL to provide a Go‑native job queue with true transactional guarantees, high concurrency via goroutines, and efficient scheduling using SKIP LOCKED, while offering step‑by‑step setup and code examples for rapid adoption.
The article compares PostgreSQL and MySQL, highlighting PostgreSQL's richer data types, native sequence support, powerful extensions, superior monitoring and replication features, and open‑source licensing, while also noting MySQL's simplicity and ecosystem strengths, to explain why many Chinese enterprises choose PostgreSQL for their core databases.
This article walks through the strengths, typical use cases, and Python connection code for relational databases (MySQL, PostgreSQL, SQLite), NoSQL stores (MongoDB, Redis, Neo4j), cloud‑native options (DynamoDB), and emerging vector databases such as Milvus, helping you decide which fits your project.
Choosing between PostgreSQL and MySQL isn’t just a feature checklist; it requires weighing business complexity, team expertise, and future uncertainty, with this guide offering core design philosophies, multi-dimensional capability comparisons, actionable decision paths, and real-world case studies to help you make a production-grade database choice.
The article compares PostgreSQL and MySQL across data types, sequence handling, extensions, monitoring tools, replication, licensing, and MVCC implementation, showing why many Chinese tech giants prefer PostgreSQL for complex, high‑availability workloads while acknowledging MySQL’s strengths in simple web scenarios.
The article explains how PostgreSQL has evolved from a simple relational store into a versatile platform that supports full‑text search, vector similarity, geospatial queries, JSONB, message queues, and analytical workloads, allowing developers to replace multiple specialized tools with a single unified system.
The article shares a seasoned DBA’s firsthand comparison of MySQL and PostgreSQL, covering their histories, performance quirks, real‑world case studies, lock mechanisms, backup strategies, and practical selection guidelines to help developers decide which database best fits their workload.
Using random UUID primary keys forces PostgreSQL to write to unpredictable index pages, causing heavy CPU usage, large index size, and dramatically higher insert latency, while switching to a sequential bigint key restores performance and reduces write amplification.
An in‑depth comparison of PostgreSQL and MySQL examines how primary and secondary indexes are implemented, contrasts query execution costs, explores data type impacts, explains MVCC undo logs, and discusses process versus thread architectures, highlighting performance trade‑offs for each system.
This guide walks developers through the fundamentals of database indexes, explaining why they matter, how they work, common pitfalls, and best‑practice design tips with concrete SQL examples and visual illustrations.
This article compares SQLite and PostgreSQL, presents detailed SQLite version timelines and OS compatibility tables, explains the differences between rollback‑journal and WAL concurrency models, shows a simple multi‑process lock test, and concludes that SQLite 3.45 is the most suitable choice for modern Linux, macOS, Android and iOS deployments.
This guide explores the fundamentals of database indexing, answering ten common questions about index design, performance pitfalls, composite indexes, covering indexes, NULL handling, and maintenance, while providing practical SQL examples, B+‑tree concepts, and best‑practice recommendations for MySQL and PostgreSQL.
With MySQL 8.0 support ending on April 30, 2026, users must migrate within six months to avoid security risks, and can choose upgrading to the latest MySQL, switching to Percona Server, or moving to alternatives like MariaDB or PostgreSQL, each with its own pros and cons.
This article examines why major Chinese technology companies are building distributed, cloud‑native and HTAP databases on PostgreSQL instead of MySQL, detailing PostgreSQL's richer data types, true sequence support, extensive extensions, superior monitoring tools, and robust replication mechanisms.
MySQL 8.0 will lose Oracle support on April 30, 2026, ending security patches, bug fixes, and official assistance, so organizations must choose between upgrading to a newer MySQL version, switching to Percona Server, or migrating to alternative databases like MariaDB or PostgreSQL.
This article presents a detailed performance benchmark comparing MySQL 9.0 and PostgreSQL 17.0, measuring data‑ingestion latency, throughput, saturation, CPU and memory usage, as well as query efficiency, and concludes which open‑source database delivers superior write and read performance.
This comprehensive guide walks you through troubleshooting PostgreSQL physical (stream) replication, covering environment prerequisites, anti‑pattern warnings, step‑by‑step diagnostics for replication lag, split‑brain scenarios, replication slot problems, monitoring setup with Prometheus, and best‑practice recommendations to keep your primary‑standby cluster healthy.
When a sudden 38% rise in AWS bills revealed hidden connection‑storm costs in a Kubernetes‑based microservice architecture, the team introduced PgBouncer as a transaction‑pooling proxy, slashing database connections from over 14,000 to under 400 and cutting monthly cloud spend by more than $300,000, ultimately saving $10.8 million over three years.
This article explains why database expenses balloon, then walks through ten practical techniques—including smart indexing, selective column queries, caching, partitioning, archiving, data‑type tuning, simplifying joins, regular maintenance, query monitoring, and right‑sized hardware—to cut costs up to 60% while preserving or even boosting query speed.
A Java backend service was unexpectedly showing a three‑day unblocking date instead of two, due to a one‑second overflow when converting LocalDateTime to java.util.Date for a PostgreSQL timestamp column, and the article walks through diagnosis, replication, and two practical fixes.
This comprehensive guide compares MySQL, PostgreSQL, and MongoDB across core features, transaction models, indexing, scalability, and real‑world use cases, offering a step‑by‑step selection method, detailed pros and cons, and a practical decision flowchart to help engineers pick the right database for their projects.
This guide explains what n8n is, compares it with Coze and Dify, and provides step‑by‑step instructions for quick installation via npx or Docker, detailed multi‑stage Dockerfile, production environment settings, database, SSL, Redis, monitoring, and backup strategies for reliable workflow automation.
This article explains how to improve the performance of large PostgreSQL IN queries by splitting them into smaller batches, executing them concurrently with Spring AOP and custom annotations, and then merging the results, providing a reusable solution for high‑volume database operations.
After disabling Redis in production and carefully testing on PostgreSQL 18, the author reduced p95 latency, simplified the system, and lowered operational overhead by replacing the cache with a covering index, a generated column, and a materialized view, while providing detailed query examples, configuration tweaks, and performance measurements.
This article examines why PostgreSQL is often a better choice than MySQL for high‑performance workloads, covering architectural differences, indexing capabilities, query optimization, data types, concurrency control, benchmark results, and migration considerations, and provides code examples to illustrate each point.
This article explains how PostgreSQL and MySQL store IP addresses using native data types and functions, showing example table definitions, insertion and query statements for both IPv4 and IPv6, and highlights the advantages of using specialized types over plain VARCHAR.
Learn how to create self-contained batch scripts that initialize a PostgreSQL database, import SQL, and launch a Spring Boot JAR on Windows, enabling one‑click service startup without manual environment configuration, and see example directory layout and customization tips.
This article compares PostgreSQL and MySQL, covering their definitions, core similarities, key differences in performance, scalability, features, ecosystem, and community, and provides practical guidance on selecting the right database for various project scenarios.
Uber migrated its core database from PostgreSQL to MySQL because PostgreSQL suffered from index bloat, write amplification, high replication overhead, and limited MVCC support, prompting a detailed analysis of each issue, the improvements in newer PostgreSQL releases, and how MySQL’s architecture addresses these challenges.
This article compares PostgreSQL and MySQL across architecture, indexing, query optimization, data types, concurrency control, and real‑world benchmarks, showing why PostgreSQL generally outperforms MySQL in high‑throughput, complex‑query, and data‑intensive applications.
This article compares how Oracle, MySQL, and PostgreSQL generate, view, and interpret execution plans, highlighting differences in hint support, caching, query efficiency, and providing practical commands and visual examples to help DBAs diagnose and optimize database performance.
While MySQL remains a reliable, widely-used relational database for simple applications, PostgreSQL’s extensibility, AI-friendly extensions, and growing developer preference—highlighted by recent Stack Overflow surveys—make it the stronger choice for modern, complex workloads, especially those involving vector search, time‑series, and geospatial data.
This article compares PostgreSQL and MySQL across architecture, indexing, complex query optimization, data‑type support, transaction handling, and real‑world benchmark results, showing why PostgreSQL is generally the better choice for high‑concurrency, data‑intensive applications.
While MySQL has long dominated relational databases with its open‑source stability and massive user base, the rise of AI and PostgreSQL’s extensible ecosystem—highlighted by extensions like pgvector, pg_bm25, TimescaleDB and PostGIS—are shifting developer preference, as shown by the 2025 Stack Overflow survey.
PostgreSQL 18, released on September 25 2025, introduces developer‑focused features such as native UUID v7 generation, virtual generated columns, enhanced RETURNING clauses, automatic BUFFERS in EXPLAIN ANALYZE, and a unified pg_get_acl() permission function, all aimed at improving everyday database development.
PostgreSQL’s index system, officially called a B‑Tree, actually implements B+‑tree functionality, storing only TIDs in leaf nodes, using linked leaf pages for efficient range queries, and includes optimizations like deduplication, index‑only scans, and reverse‑key indexes to boost performance.
This comprehensive guide explains PostgreSQL streaming replication concepts, required environment, primary and standby configuration commands, verification queries, failover procedures, and production best‑practice recommendations, enabling you to build a reliable high‑availability database cluster.
PostgreSQL 18 introduces async I/O for faster queries, built‑in OAuth authentication, expanded SQL standard support, optimizer and extension enhancements, and tighter Kubernetes integration, delivering higher performance, stronger security, and greater flexibility for developers and DBAs tackling modern analytics, AI workloads, and distributed environments.
This guide explains how to bypass interactive password prompts when using psql by configuring a per‑user .pgpass file, setting the PGPASSWORD environment variable for temporary sessions, and adjusting the server‑side pg_hba.conf file, while covering required file formats, permission settings, security trade‑offs, and best‑practice recommendations.
This comprehensive guide walks you through installing PostgreSQL on Linux, Windows, macOS, and Docker, configuring users, databases, and remote access, using daily psql commands, performing backups, applying advanced features like tablespaces and replication, and optimizing performance with key tuning parameters.
This article introduces PostgreSQL's powerful features and provides detailed, cross‑platform instructions for preparing the host, configuring network interfaces, adjusting system settings, and installing PostgreSQL via native packages or official repositories on major Linux distributions.
Based on a survey of over 30,000 Python developers, the 2025 report shows half are newcomers, AI‑assisted coding is exploding, FastAPI leads web frameworks, most still run legacy versions, Rust‑based tools gain traction, and PostgreSQL remains the dominant database, shaping Python’s future direction.
This article compares MySQL and PostgreSQL by outlining their histories, architecture differences, benchmark results for SELECT, INSERT, and UPDATE operations, and discusses which scenarios each database best fits, helping readers decide which system to adopt for their projects.
This article compares MySQL and PostgreSQL by outlining their architectures, presenting benchmark results that show PostgreSQL’s superior throughput and latency, and discussing the scenarios where each database shines to help developers decide which one fits their project best.
A Java backend bug caused blacklist unblocking times to be stored one second later than expected due to mismatched Date and TIMESTAMP precision, daylight‑saving and timezone conversions, and millisecond rounding, which was diagnosed through code review, AI analysis, and batch testing, then fixed by normalising nanoseconds or adjusting database column precision.
