mgramin/awesome-db-tools

Everything that makes working with databases easier

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Summary Information

Updated 28 minutes ago
Type:Curated List / Learning ResourceCategory(s):General Awesome Lists & DirectoriesLearning & Resources
Added to GitGenius on September 12th, 2026
Created on May 18th, 2018
Open Issues & Pull Requests: 202 (+0)
GitHub issues: Enabled
Number of forks: 498
Total Stargazers: 5,327 (+0)
Total Subscribers: 72 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 16.8 hours
Mean response time: 393.7 days
90th percentile: 1542.8 days
Tracked items: 8

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Issue Activity (beta)

Open issues: 18
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 430 days
Stale 30+ days: 18
Stale 90+ days: 18

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Awesome Database Tools is a curated list that collects database tools across multiple categories and use cases.

The project addresses the challenge of discovering and evaluating the wide variety of tools available for database work. It organizes tools by function—including IDEs, GUI clients, CLI tools, schema management, monitoring, backup, security, SQL utilities, and data handling—making it easier for database professionals to find relevant solutions for specific problems rather than searching through scattered resources.

This list suits anyone working with databases who needs to evaluate options: database administrators, DevOps engineers, developers, and those new to database management. The breadth of categories means it covers specialized needs like high-availability setup, Kubernetes integration, performance tuning, and data lineage tracking alongside general-purpose tools. The community-driven model allows contributors to add their own tools or recommend favorites, so the collection reflects practical, in-use solutions rather than theoretical options.

The project maintains an organized, categorized structure that grows through community contributions. It serves as a reference point rather than a tool itself, functioning as a discovery mechanism for the broader database tooling ecosystem.