
MariaDB started as a fork of MySQL back in 2009 when Oracle acquired Sun Microsystems. At the time, people weren't sure if the fork would survive long-term or just become another abandoned open source project. Fast forward to 2026 and MariaDB has become a serious alternative that many developers now prefer over the original. This article looks at why.

Choosing between MySQL and PostgreSQL isn't straightforward. Both are mature, production-ready databases used by companies of all sizes. But they solve problems differently and each has strengths that matter depending on your use case. This article breaks down the actual differences that affect day-to-day development and operations in 2026.

Performance tuning isn't about following a checklist. It's about understanding what's actually slowing down your database and fixing those specific problems. These are techniques that consistently deliver real improvements in production environments. Some of them are obvious but frequently misconfigured. Others are less known but surprisingly effective.

Losing data hurts. Whether it's a corrupted disk, accidental deletion, or a bad deployment that wipes your production database, recovery without backups means starting from scratch. Automated PostgreSQL backups remove the human factor from the equation. You set them up once, and they run reliably while you focus on other things.

Running MongoDB in Docker simplifies deployment and makes environments reproducible across development, testing and production. You can spin up a database in seconds without dealing with complex installation procedures. This guide covers everything from basic container setup to production configurations with replica sets, persistence, custom settings and proper backup strategies.
Running MariaDB in Docker simplifies deployment, makes environments reproducible, and allows you to spin up databases in seconds. Whether you need a quick dev environment or a production-ready setup, Docker handles the complexity of installation and configuration. This guide covers everything from basic container setup to production configurations with persistence, custom settings and proper backup strategies.

Storing MySQL backups on the same server as your database is asking for trouble. If the server fails, you lose both your data and your backups. Cloud storage solves this by keeping backups offsite, automatically replicated across multiple data centers. This guide covers how to back up MySQL databases to AWS S3 and Google Cloud Storage, from manual uploads to fully automated pipelines.

Keeping every backup forever sounds safe until you see the storage bill. A PostgreSQL database with daily backups accumulates 365 files per year, and monthly backups over a decade add up too. Retention policies define which backups to keep and which to delete, balancing recovery options against storage costs. This guide covers practical retention strategies for PostgreSQL, from simple time-based rules to grandfather-father-son schemes and compliance-driven requirements.

Database backups grow quickly. A PostgreSQL database that starts at a few gigabytes can balloon to hundreds of gigabytes over time, and backups multiply that storage requirement. Compression reduces backup sizes by 70-90% in most cases, cutting storage costs and speeding up transfers. This guide covers the practical compression options available for PostgreSQL backups, from built-in pg_dump compression to external tools and automated solutions.

Backing up MongoDB manually works fine until you forget to do it. And that usually happens right before something breaks. Automated backups remove the human factor from the equation and ensure your data is protected consistently. This guide covers several approaches to automating MongoDB backups, from simple cron jobs to dedicated backup tools.