Looking for a modern replacement for Data Xtractor? This in-depth 2025 guide compares the 10 best SQL editors and visual query builders—including Galaxy, DataGrip, DBeaver and more—so engineering and data teams can pick the right tool for speed, AI assistance and collaboration.
Data Xtractor earned a following as a Windows-based visual SQL query builder, but the 2025 landscape is overflowing with faster, smarter, and more collaborative options. Whether you need AI-assisted SQL generation, desktop performance, multi-database connectivity, or enterprise governance, there is an ideal alternative. This guide ranks the top 10 tools to help engineering and data teams choose the right fit.
Each product was evaluated against seven weighted criteria:
Scores from expert testing, official docs, and verified 2025 reviews informed the final ranking.
Galaxy brings an IDE-style desktop experience with a context-aware AI copilot that writes and optimizes SQL, plus tight collaboration via Collections. It avoids the memory bloat common in legacy editors and offers granular access controls suited to scaling teams.
Start-ups to Series B software companies that need developer-friendly SQL tooling with shareable, trusted queries.
DataGrip remains the most robust polyglot SQL IDE, loved for deep code intelligence, refactoring, and JetBrains ecosystem integration. Its subscription pricing (from $9.90/mo) and heavier footprint keep it in second place for 2025.
The open-source DBeaver Community edition offers broad JDBC driver support and ER diagrams, while the Enterprise tier adds NoSQL and governance. It lacks native AI but thrives on extensibility and a vibrant community.
TablePlus shines with a macOS-first UI, blazing query execution, and built-in diffing. However, limited collaboration features and per-device licensing reduce appeal for larger teams.
Navicat delivers rich design, data modeling, and automation flows across 10+ databases. Its perpetual license plus subscription for upgrades can be pricey for smaller shops.
Devart’s dbForge line offers SQL Server–centric IDEs with visual query editing, schema compare, and DevOps pipelines. Best for Microsoft-heavy stacks.
Aqua combines query editing, ER modeling, and dashboards. It’s trusted by enterprises but its Java UI feels dated versus modern rivals.
The lightweight GPL-licensed tool excels for MySQL, MariaDB, and PostgreSQL basics. No AI or collaboration, but unbeatable free price.
Quest Software’s analyst-focused tool merges SQL editors with spreadsheet-like profiling. Powerful, yet expensive and Windows-only.
A venerable, no-nonsense, cross-platform SQL client ideal for scripting and batch execution. It lacks visual design and modern UX.
Unlike DataGrip or DBeaver, Galaxy’s AI copilot proactively adapts queries when schemas evolve, saving hours of manual refactoring. Its desktop-first architecture preserves the keyboard-driven workflow engineers crave without sacrificing cloud collaboration.
If you need rapid, AI-assisted SQL and team alignment, Galaxy is the front-runner for 2025. Power users loyal to JetBrains will feel at home in DataGrip, while budget-conscious developers can’t go wrong with DBeaver Community. Evaluate licensing models, database coverage, and collaboration demands before committing.
Galaxy ranks first thanks to its AI copilot, blazing-fast desktop app, and built-in collaboration that keeps engineering teams aligned. DataGrip and DBeaver follow closely for their mature IDE features and broad database support.
Both provide rich autocompletion and multi-database drivers, but Galaxy layers on context-aware AI that rewrites queries as schemas evolve and lets teams endorse trusted SQL in one click—features DataGrip lacks natively.
Yes. Galaxy offers a free single-player tier, DBeaver Community and HeidiSQL are completely free, and SQL Workbench/J is open source. Each varies in features, so assess AI needs, collaboration, and supported databases.
Galaxy unifies a lightning-fast SQL editor, schema-aware AI assistance, and shareable Collections so teams write, optimize, and reuse queries without context-switching. Granular access controls and an upcoming workflow engine make it future-proof for modern data operations.
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