Physical and incremental backups with WAL streaming for Point-In-Time-Recovery were released in Databasus

Happy to share Databasus reached 6000 stars on GitHub! ⭐️

Really thank you @AnthropicAI and @OpenAI for supporting open source projects There are completitions between you. But anyway, you together have changed the world of development latest years Now it is not possible to imagine development without your AIs de-facto

Appeared that @OpenAI released program Codex for Open Source We applied and Databasus received support from Open AI as well. Thank you guys! Soon Codex Security will be integrated into our PRs review process on GitHub

Really happy to share that @AnthropicAI supports Databasus through their Claude for Open Source program! For those who have not heard about Databasus yet: it's a PostgreSQL backup tool. Recently, support of MySQL, MariaDB and MongoDB has been added as well. Now the project has about ~250k Docker Hub pulls and 5.8k GitHub stars Website - databasus.com GitHub - github.com/databasus/databas… It means a lot when a company like Anthropic recognizes the work behind an open-source project. Databasus started as a small internal tool for backing up Postgres databases, and now it's used by hundreds of thousands of people and teams around the world. Having this kind of support is genuinely motivating and helps me keep going Thank you, Anthropic. I appreciate it - as well as all the maintainers of open-source projects out there. Your work has already changed the world of development P.S. Claude is used a lot in the development process of Databasus, but the project has strict guidelines about how AI is used. No vibe coding, no AI-written code without line-by-line human review, no code without tests. Every PR goes through CI/CD and manual verification You can read full AI policy in the README: github.com/databasus/databas… It's important to use the power of AI consciously and treat it as a tool, not a crutch.

I want to share the latest important updates for my open source tool for scheduled databases backup (with focus on PostgreSQL). A quick recap: - Supported databases: PostgreSQL, MySQL, MariaDB and MongoDB - Many storage destinations: local storage, S3, Google Drive, Dropbox, SFTP, rclone and more - Notifications: Slack, Discord, Telegram, email, webhook In 2025 Databasus renamed from Postgresus when it became popular and support for other databases was added. Primary audience for the project is developers, DevOps engineers and DBAs. Now project is the most GitHub starred repository for backups (surpassed even WAL-G and pgBackRest). There are ~240k pulls from Docker Hub (both of previous Postgresus and Databasus images). New features: 1. GFS retention policy GFS is an acronym for Grandfather-Father-Son. It allows to keep last N hourly, daily, weekly, monthly and yearly backups. This is needed to keep backups over wide period of time within reasonable storage space. Before only X days or months were supported. By default now is used: - Keep 24 hourly backups - Keep 7 daily backups - Keep 4 weekly backups - Keep 12 monthly backups - Keep 3 yearly backups 2. Encrypted backups are stored along with their metadata to decrypt them without Databasus itself Before, if server with Databasus is destroyed, you were not able to decrypt backups without Databasus itself. So you had to make backups of Databasus internal DB. Now backups are stored in S3\Google Drive\other storages with meaningful names with their encryption metadata in format: - {database-name}-{timestamp}-{backup-id}.dump - {database-name}-{timestamp}-{backup-id}.dump.metadata In case of server destruction, you need only `secret.key` to decrypt backups and restore via pg_dump, mysqlbackup, mongodump or other tools. Full guide - databasus.com/how-to-recover…

New feature: GFS retention policy (Grandfather - Father - Son) Now you can keep more history with less space using automatic rotation: - 24 latest hourly backups - 7 daily backups - 4 weekly backups - 12 monthly backups (~1 year) ✅ Best for: long-term archiving, audits, rollback safety - without bloating storage. Retention tiers are configurable to match your needs

Databasus just shipped full backup portability. Your backup files can now be restored using only standard tools — no Databasus required. If your instance ever goes down, your data is still fully recoverable from any storage you use. See docs - databasus.com/how-to-recover…

Databasus appeared as a PostgreSQL backup tool in awesome sysadmin GitHub's directory - github.com/awesome-foss/awes… One more large open source projects directory included Databasus! 🕶️

PostgreSQL backup tool Databasus reached 5000 stars on GitHub! This is noticeable step for databases open source tooling world!

Databasus increased CI \ CD speed for ~40% via switching to self hosted GitHub Actions runner with AMD Ryzen 9 7950X The project use GitHub Actions to: - enforce code quality (linting, build checks) - testing (both backend and frontend, overall ~1k tests right now) - building and publishing images to Docker Hub (x64 and ARM) Over testing, 40 Docker containers are launched to perform E2E and integration tests (on all supported PostgreSQL, MySQL, MariaDB and MongoDB versions). See docker-compose.yml here - github.com/databasus/databas… Before process usually tool ~25-22 minutes for CI \ CD pipeline. Of corse, with all possible caching, parallel jobs, etc. Right now Databasus switched to VPS with AMD Ryzen 9 7950X. This is one of the most powerful CPUs per core without "energy optimized" cores. Btw, this is the CPU stays in my dev PC :) So now CI \ CD pipeline is executed for about 13-15 minutes. It's around ~40% increase in speed via just changing hardware

Hi Here I (@rostislav_dugin) will write about development of Databasus Just to remind: Databasus is an open source tool for scheduled PostgreSQL backups. Save backups to different storages (local, S3, Google Drive, etc.) and receive notifications via Slack, MS Teams, email, Discord, etc. Website - databasus.com GitHub - github.com/databasus/databas…