Top 12 SQL Editors and IDEs for 2025: The Best Database Clients for Every Need

Writing SQL queries is a core part of working with databases, and having the right SQL editor or IDE can greatly boost your productivity. Whether you’re a software developer, data analyst, or database administrator, a good SQL client provides features like syntax highlighting, autocompletion, error checking, and query results visualization. In 2025, there are many options to choose from – from lightweight free SQL clients to full-featured commercial SQL IDEs – so finding the best SQL editor for your needs is important.

In this article, we’ll compare the top SQL IDEs and editors available today, including tools for Mac, Windows, and Linux. We rank our Top 12 SQL Editors for 2025, highlighting key features, pros and cons, platform compatibility, and pricing for each. Whether you need a free SQL client for basic tasks or a collaborative SQL IDE with AI assistance, you’ll find an option here. (If you’re just getting started with SQL, check out our SQL learning resources and SQL interview prep guide for fundamentals and practice. You can also refer to our SQL Glossary for quick definitions of key terms.)

Now, let’s dive into the best SQL editors of 2025 and see how they stack up.

1. Galaxy

Galaxy is a modern, collaborative SQL IDE designed for today’s development and analytics teams. It’s a web-based platform (no installation required) that combines a blazing-fast SQL editor with built-in AI assistance and real-time collaboration. Galaxy supports all major databases (from PostgreSQL and MySQL to modern cloud data warehouses) and allows you to write, save, and share queries effortlessly. Unlike traditional desktop clients, Galaxy lets multiple users work together on queries in real time – similar to Google Docs, but for SQL – making it perfect for team environments. It also offers context-aware AI suggestions (an "AI co-pilot") to help you generate and optimize SQL queries, which is especially handy for complex joins or unfamiliar schemas. Overall, Galaxy is built to streamline SQL exploration for developers and data analysts alike, with a focus on speed, intelligence, and teamwork.

Key Features:

• AI Autocomplete & Chat: Galaxy’s editor comes with an AI assistant that can auto-complete your code and even generate SQL from plain English prompts. This context-aware AI can suggest queries or improvements, helping you write correct SQL faster.
• Real-Time Collaboration: Multiple team members can edit and comment on the same query simultaneously. You can share query links, collaborate on analyses, and never worry about emailing SQL snippets again.
• Saved Queries & Snippets: Save your commonly used SQL queries or snippets in organized collections. Teams can build a shared library of vetted queries, so everyone can reuse work and maintain one source of truth.
• Integrations with Databases: Galaxy connects to popular databases (Postgres, MySQL, SQL Server, BigQuery, Snowflake, and more) with ease. It centralizes your connections and credentials securely, so you can query multiple data sources from one interface.
• Performance & UX: Built with modern technologies, Galaxy’s web interface feels snappy even on large datasets. Features like syntax highlighting, error highlighting, and results grid with quick filtering are all standard, providing a smooth querying experience.

Pros:

• Collaborative by Design: Ideal for teams – no other SQL editor offers such seamless real-time collaboration and sharing of queries.
• AI-Powered Productivity: The AI SQL co-pilot can dramatically speed up query writing and help users learn SQL patterns or best practices on the fly.
• Cloud-Based Convenience: Runs in the browser, so there’s nothing to install and you always have the latest version. It works on any OS and can be accessed anywhere.
• Modern Interface: Galaxy’s UI is clean and intuitive, with useful touches like dark mode, keyboard shortcuts, and one-click charting of query results. It feels much more polished than some older tools.
• Security & Control: Designed for enterprise use with features like access controls, audit logs of query runs/edits, and end-to-end encryption of data connections.

Cons:

• New Product: As a newer platform (launched in 2025), Galaxy is still evolving. It may not yet have some very niche features or plugins that long-standing IDEs offer (though its rapid development is adding features quickly).
• Internet Required: Since it’s a cloud tool, you need an internet connection to use Galaxy. (On the upside, this also means no local setup hassles and easy collaboration.)
• Beta Stage: Currently in early access, users might encounter minor bugs as the team fine-tunes the product. However, updates are frequent and responsive to feedback.

Platforms: Web (runs in all modern browsers on Mac/Windows/Linux). Pricing: Free tier available for individuals and small teams; paid plans (Pro/Enterprise) unlock higher usage and advanced admin features.

2. JetBrains DataGrip

JetBrains DataGrip is a powerful cross-platform SQL IDE known for its intelligent code assistance and deep database refactoring capabilities. It’s part of the JetBrains family of developer tools (the makers of IntelliJ IDEA), and it provides a unified interface to work with various relational databases. DataGrip runs on Windows, macOS, and Linux, and it supports all common DBMS via JDBC drivers – including PostgreSQL, MySQL/MariaDB, Oracle, SQL Server, SQLite, and many others. For developers who are already using JetBrains IDEs, DataGrip feels familiar and integrates well into their workflow. It offers advanced features like contextual code completion (aware of your database schema), real-time error detection in SQL code, and the ability to refactor database objects (e.g., rename a column across all queries) safely. This makes DataGrip one of the best SQL IDEs for heavy-duty database development and complex projects where productivity and correctness are paramount.

Key Features:

• Smart Code Completion: DataGrip understands your database schema and suggests table names, column names, and SQL functions as you type. It can even suggest join conditions based on foreign keys, helping to write queries faster and with fewer errors.
• Refactoring and Analysis: You can refactor database objects through the IDE (for example, rename a table or column), and DataGrip will preview and update all affected SQL queries. It also analyzes queries for potential issues and highlights SQL errors or suspicious logic in real time.
• Multiple Database Support: Manage all your databases in one tool. DataGrip lets you connect to numerous databases concurrently and organize them in a tree view. You can run queries, edit data, and compare schemas across different DB types seamlessly.
• Integrated Tools: It provides capabilities like a table data editor (for browsing and editing table rows in a spreadsheet-like view), import/export wizards, query result visualizations, and version control integration for SQL scripts. Recent versions even experiment with AI-assisted coding (via JetBrains AI features) to further boost productivity.
• Customization: As with other JetBrains IDEs, you can customize keymaps, themes, and plugins. DataGrip supports many plugins (including Docker integrations, VCS, and language injections), allowing you to tailor the environment to your needs.

Pros:

• Extremely Powerful IDE: DataGrip is built for professional developers—its advanced SQL insight and refactoring tools are unmatched, preventing mistakes like misspelled column names or forgotten join conditions.
• Polyglot Support: It works with a broad array of SQL dialects and even NoSQL (via plugins), making it a one-stop shop as your SQL client for all databases. No need to switch tools when working with multiple systems.
• Productivity Features: Little touches like SQL formatting, code snippets, parameter hints, and integration with source control make working on SQL codebases more efficient. It’s great for maintaining large SQL scripts or database projects.
• Frequent Updates: JetBrains regularly updates DataGrip with new features, database driver updates, and performance improvements. User feedback is often incorporated, keeping the IDE current with industry needs.

Cons:

• Not Free: DataGrip requires a paid subscription (either standalone or via JetBrains All Products Pack). While reasonably priced for professionals, this can be a barrier for students or hobbyists (though JetBrains offers free licenses for academia and open source contributors).
• Heavy Application: Being a full IDE, it is more resource-intensive than simpler editors. It can be slow to launch and consumes considerable memory, especially when multiple databases or large projects are open.
• Learning Curve: New users might find the multitude of features overwhelming. It takes time to discover and use advanced functionalities (though basic querying is straightforward). Users not familiar with JetBrains’ interface may need some acclimation.
• Lacks Collaboration: DataGrip is a single-user desktop application with no inherent collaboration or sharing features. It’s geared towards individual developer productivity, not real-time team collaboration.

Platforms: Windows, macOS, Linux. Pricing: Commercial (approximately $8–$20 per month per user, depending on plan; free trial available, and free for qualified students/OSS projects).

3. DBeaver

DBeaver is one of the most popular free SQL clients and database management tools, renowned for its versatility. It’s an open-source, cross-platform application (Java-based) that supports virtually every relational database (Postgres, MySQL/MariaDB, SQLite, Oracle, SQL Server, DB2, etc.) and even some NoSQL databases via extensions. DBeaver’s “Community Edition” is fully free and feature-rich, which has made it a go-to choice for developers and data engineers worldwide. It provides a classic desktop GUI to browse database schemas, run SQL queries, and manage various database objects. Despite being free, DBeaver offers many capabilities found in paid tools – from ER diagrams and SQL execution plans to a robust CSV export/import and data editing interface. There’s also an Enterprise Edition (paid) that adds support for additional databases and collaboration features, but the free version is sufficient for most use cases.

Key Features:

• Universal Database Support: DBeaver can connect to a wide range of database systems through JDBC drivers. Users can easily add new connections, and DBeaver often auto-detects drivers or downloads them. This makes it possible to work with PostgreSQL, MySQL, Oracle, SQLite, Teradata, Firebird, and many others in one tool.
• SQL Editor and Result Viewer: It offers a robust SQL editor with syntax highlighting, code completion, and execution of scripts. Query results are shown in a grid where you can sort, filter, and even edit the data directly. You can also view results as charts or JSON/XML for certain data types.
• ER Diagrams and Database Modeling: You can visualize database schemas with DBeaver’s ER diagramming tool, which helps in understanding table relationships. It also allows generating schema DDL scripts, comparing schemas, and migrating data between databases.
• Extensibility: DBeaver supports plugins (it’s built on the Eclipse platform). This means users can extend its functionality or integrate it with other tools. For example, there are extensions for Git version control, for MongoDB, for AWS S3 data, etc. This plug-in architecture makes DBeaver highly adaptable.
• Data and Admin Tools: It includes many handy tools like a database connection manager (with secure credential storage), data import/export wizards (to CSV, XLS, etc.), query execution plans for performance tuning, and support for executing scripts in batches. The enterprise version even adds things like mock data generation and web-based collaboration.

Pros:

• Free & Open Source: The community edition of DBeaver is free for everyone, with an active community contributing to its improvements. This makes it excellent for budget-conscious users or open-source enthusiasts.
• Cross-Platform: Works on all major OSes (written in Java). A developer can have the same tool on their Windows PC at work and Mac/Linux at home, ensuring a consistent workflow.
• Feature-Rich: Despite zero cost, DBeaver has a comprehensive feature set. It can handle most tasks – from simple query running and editing data, to complex tasks like migrating databases. It’s often cited as a great alternative to paid clients.
• Large Community & Support: With millions of users, there are plenty of online resources, tutorials, and community support for DBeaver. It’s regularly updated and bug-fixed by its maintainers.

Cons:

• UI Complexity: The interface, while powerful, can feel cluttered or less intuitive, especially to newcomers. It adheres to a more technical, form-based UI (inherited from Eclipse) rather than a sleek modern design.
• Performance: Being Java-based, DBeaver can sometimes be slow to start up and may use significant memory with large datasets or multiple connections. It’s not as lightweight as some native clients (although performance is generally good once running).
• Limited Collaboration: Out of the box, it’s a single-user tool. You cannot natively share queries or collaborate in real-time (you’d have to share SQL files manually). The focus is on individual use, unless you opt for the paid team features.
• Learning Overhead: For very simple use cases, DBeaver might be overkill. Users looking for a minimalist query runner might find the myriad of options overwhelming if they don’t need them all.

Platforms: Windows, macOS, Linux. Pricing: Free (open-source Community Edition). Enterprise Edition available with extra features (subscription per user, optional).

4. TablePlus

TablePlus is a modern, native GUI client for databases that emphasizes speed and a clean user experience. Initially launched on macOS, it has since expanded to Windows and Linux, offering a uniform yet native-like experience on each platform. TablePlus supports a variety of popular relational databases out of the box: MySQL, PostgreSQL, MariaDB, SQLite, Microsoft SQL Server, Redis (for key-value browsing), and more through community plugins. One of TablePlus’s standout qualities is its performance – it’s written in native code (not Java or Electron), which makes it extremely fast and lightweight. The interface is sleek and minimalistic, making it easy to open a new connection and start querying without much configuration. It’s a favorite especially among Mac users and developers who want a hassle-free, aesthetically pleasing SQL client.

Key Features:

• Native UI & Speed: TablePlus leverages native frameworks on each OS, resulting in a snappy application. It launches quickly and executes queries swiftly. The UI feels at home on Mac and Windows – including dark mode, keyboard shortcuts, and drag-and-drop functionality.
• Multiple Database Support: You can manage multiple connections, each in a separate tab or window. TablePlus can handle connections to different types of databases simultaneously, and it lets you visually navigate schemas, tables, and records easily.
• Built-in Productivity Tools: It includes a powerful SQL editor with syntax highlighting and instant autocompletion. There’s a convenient filter on tables to quickly find data, a query history log, and the ability to save queries. TablePlus also supports exporting results or tables to CSV/JSON and other formats.
• Secure Connection Management: The tool provides features like SSH tunneling for connecting to databases behind firewalls, and it can store passwords securely using the operating system’s keystore (Keychain on Mac, etc.). This makes connecting to remote databases safe and straightforward.
• Customizable Appearance & Plugins: Users can customize the interface (themes, font, etc.). While TablePlus is not open-source, it does allow community plugin extensions and has an API for adding features. This extensibility means features like a JSON view or new drivers can be added by users.

Pros:

• Blazing Fast and Lightweight: TablePlus is optimized for speed. It consumes fewer resources and delivers quick response times, which is noticeable when working with large tables or switching between multiple connections.
• User-Friendly Design: The polished UI with intuitive icons and layout reduces the friction in browsing databases. Even less-experienced users find it approachable for executing queries or inspecting data.
• Cross-Platform Availability: Now available on Mac, Windows, and Linux, it caters to teams that use different OS environments, while still preserving that native feel on each. (There’s even an iOS app for on-the-go access.)
• Freemium Model: You can use TablePlus for free with some limitations (like a cap on the number of tabs or saved connections). This is great for trying it out indefinitely on small projects. A one-time purchase unlocks all features, which many appreciate over recurring subscriptions.

Cons:

• Limited Advanced Features: TablePlus focuses on core use-cases (querying and browsing). It doesn’t include advanced data modeling, query explain plans, or profilers out-of-the-box like some heavier IDEs. Power users may find it lacking certain tools for deep database tuning or development.
• No Collaboration Features: The application is single-user. If you need to share queries or results, you have to export or copy them manually. It’s not a collaborative platform and does not have built-in version control for queries.
• Primarily GUI-Oriented: While the GUI is great, automation or scripting support is minimal compared to something like using psql or scripts. Users who prefer a hybrid of GUI + scripting might find TablePlus more limited in that regard.
• Support & Licensing: TablePlus is developed by a small team. While they are active, enterprise-level support or continuous integration features are not as formalized as in some enterprise tools. Also, the free version’s limits (e.g. max 2 tabs open at once) can be inconvenient until you buy a license.

Platforms: macOS, Windows, Linux (plus an iOS app). Pricing: Free to use with feature limitations; paid license ~$99 (one-time) per user for unlimited use and premium features.

5. Beekeeper Studio

Beekeeper Studio is a free, open-source SQL editor that has quickly gained popularity for its attractive interface and ease of use. It’s a cross-platform desktop application (available on Windows, Mac, and Linux) built with Electron, which means it’s able to provide a modern UI with features that rival paid tools. Beekeeper Studio supports all common databases – you can connect to PostgreSQL, MySQL, MariaDB, SQL Server, SQLite, and more. The goal of the project is to offer a “slick” and intuitive SQL client that covers 90% of daily tasks without the bloat, making it ideal for developers or analysts who want something between a bare-bones tool and a heavy IDE. As an open-source project, Beekeeper Studio is continually improving and is backed by a community of contributors and users.

Key Features:

• Multi-DB Connections: Like other universal clients, Beekeeper lets you manage multiple database connections in one window. You can save connection details (with encryption) and quickly switch between different databases or servers. The tabbed interface allows running several queries on different connections concurrently.
• Query Editor & Results: The SQL editor provides syntax highlighting and pretty good autocomplete for SQL keywords and table/column names. When you run a query, results appear in a results grid where you can sort and filter. You can also open multiple result sets side by side, which is useful for comparing data.
• Table Editing: You can click on a table to view its contents and then edit data directly in the grid. This is handy for making quick data fixes. Additionally, Beekeeper has features for adding or dropping table columns, viewing constraints, and other lightweight admin tasks, all through the GUI.
• Saved Queries & History: Beekeeper Studio keeps a history of queries you’ve run, so you can easily retrieve past commands. It also allows saving queries as “favorites” or in a collection for reuse later. This is useful for not having to rewrite commonly executed statements.
• Themes and Layouts: The application includes multiple themes (dark/light) and layout options. It also supports docking panels, so you can arrange your query editor and results panels in a way that suits your workflow. The interface is designed to scale well even on high-resolution (4K) displays.

Pros:

• Completely Free & Open-Source: There’s no cost to use Beekeeper Studio, and its source code is openly available. This makes it a great choice for those who prefer open-source solutions or want to avoid license fees.
• Polished, Modern UI: Users often praise Beekeeper’s interface for being clean and appealing. It feels like a contemporary app with smooth UX, in contrast to some older open-source SQL clients. This improves the developer experience for daily tasks.
• Cross-Platform Sync (Optional): While all core features are free, the developers offer an optional paid cloud sync service that can sync your saved connections and queries across devices. This is an added convenience (completely optional) for those who work on multiple machines.
• Active Development: The project is actively maintained. Bugs are fixed frequently, and new features/community requests are often incorporated. As a result, it’s becoming more powerful with each release, closing the gap with paid tools.

Cons:

• Electron-Based: Being an Electron app, Beekeeper Studio might not be as lightweight as a native app. It uses more memory than some simpler clients (though on modern systems this is usually not a major issue). Some users might notice slightly slower UI performance with extremely large result sets compared to native clients.
• Less Extensible: Compared to a tool like DBeaver, Beekeeper doesn’t have a plugin ecosystem. What you see is what you get, so if a feature is missing (e.g., specific database management function), you might have to use another tool for that task.
• Lacks Some Advanced Tools: While it covers most querying and editing needs, it doesn’t offer advanced performance tuning tools like detailed execution plans or index advisors. Professionals needing those might use Beekeeper for everyday querying but still rely on specialized tools for deep optimization tasks.
• Single-User Focus: Like most desktop SQL clients, collaboration features are not present. It’s meant for individual use – sharing queries would require external means (copying SQL text, etc.).

Platforms: Windows, macOS, Linux. Pricing: Free and open-source for all features. (An optional paid subscription is offered for cloud sync services, but the core app remains free.)

6. MySQL Workbench

MySQL Workbench is the official GUI tool for MySQL (and its fork MariaDB), provided by Oracle. It has been a staple for MySQL developers and DBAs for many years, offering a suite of tools in one application. Workbench is cross-platform (available on Windows, Mac, Linux) and focuses specifically on MySQL/MariaDB databases. It serves multiple roles: you can design and model databases visually, execute and optimize SQL queries, and administer servers (manage users, replication, backups, etc.) all through Workbench’s interface. This all-in-one approach makes it a powerful choice for those working primarily with MySQL. While its interface isn’t the flashiest, it is robust and full-featured for MySQL-specific tasks.

Key Features:

• Visual Database Modeling: One standout feature is the ER diagram designer. You can create tables and relationships visually, and then forward-engineer the model to a MySQL database (or reverse-engineer an existing database into a diagram). This is great for planning a database schema or understanding an existing one.
• SQL Editor & Query Analyzer: MySQL Workbench includes a SQL editor with syntax highlighting and execution shortcuts. It provides an explain plan for queries (to help optimize them) and a profiling feature to measure query performance. This is useful when tuning complex SQL or indexing strategies in MySQL.
• MySQL Server Administration: The tool has a dedicated section for admin tasks. You can manage server configuration variables, create and manage user accounts and privileges, perform database backups and restores, and monitor server health (connections, status variables) – all without needing the command line.
• Data Migration Toolkit: Workbench includes a data migration wizard that can migrate tables from other database systems to MySQL. It supports converting schemas and transferring data from sources like PostgreSQL, SQL Server, SQLite, etc., which can be handy in heterogeneous environments.
• Plugins & Scripting: Advanced users can write Python or Lua scripts to automate tasks in Workbench or extend its functionality. There are also some plugins available that add extra features or integrations, given its long presence in the community.

Pros:

• Official Tool for MySQL: Being made by the MySQL team, it’s always up-to-date with the latest MySQL features and versions. You can trust it for compatibility and comprehensive support of MySQL’s capabilities (from newer JSON functions to older storage engines).
• Comprehensive Feature Set: MySQL Workbench truly covers end-to-end needs for MySQL. From design to development to administration, you can do it all in one application. This can eliminate the need to juggle multiple tools.
• Strong Community & Documentation: There is extensive official documentation and a large user base. This means if you encounter issues or want to learn how to do something in Workbench, there’s likely a tutorial or forum discussion about it.
• No Cost: It’s free to download and use, with no paid tiers. This makes it an accessible choice for anyone using MySQL, from small projects to enterprise deployments.

Cons:

• MySQL-Only: The major limitation is that it’s tailored for MySQL/MariaDB. If your work extends beyond those, Workbench won’t help with other database systems. Many developers use Workbench for MySQL alongside a different tool for other databases.
• Resource Heavy: Workbench can be demanding, especially when rendering complex ER diagrams or processing large result sets. Some users find it slow or prone to freezing when dealing with very large databases or queries.
• Interface Dated in Parts: The UI, while functional, is not as modern or streamlined as some newer clients. Certain tasks may require navigating through several panels or wizards, which can feel cumbersome. It’s a tool built for capability more than simplicity.
• Stability Issues: In the past, users have reported occasional crashes or bugs (particularly on Mac versions or when using specific features). Although it has improved, Workbench’s stability can vary depending on OS and workload.

Platforms: Windows, macOS, Linux. Pricing: Free (community edition) for all users.

7. pgAdmin 4

pgAdmin 4 is the leading open-source administration and development platform for PostgreSQL. It’s essentially the “official” PG GUI, maintained by the PostgreSQL community. pgAdmin 4 is a major rewrite (using web technologies) of the earlier pgAdmin series, and it can run as a desktop application or in server mode (accessible via browser). It provides a graphical way to interact with PostgreSQL databases: you can browse through database objects, run SQL queries, and utilize various tools to manage your Postgres server. For developers and DBAs who use PostgreSQL (or related databases like EDB Postgres, Greenplum, etc.), pgAdmin is often a go-to choice for performing tasks without needing the psql command-line for everything.

Key Features:

• Comprehensive Postgres Support: pgAdmin exposes nearly all functionalities of PostgreSQL. You can create and modify tables, indexes, views, functions, triggers, and manage extensions. The Object Browser shows all schemas and objects in a tree structure, making navigation easy for complex databases.
• SQL Query Tool: It includes a decent SQL editor with syntax coloring and some autocompletion for SQL keywords and object names. You can execute ad-hoc queries or scripts and see the results in either text or grid view. It also has an explain plan viewer to help optimize queries by visualizing the execution plan.
• Server Monitoring & Maintenance: There are tools for monitoring sessions/locks, viewing the Postgres server log, and manually triggering maintenance commands (like VACUUM, ANALYZE). pgAdmin also has a simple dashboard for each server showing charts of resource utilization, which is useful for a quick health check.
• Backup/Restore & Data Import/Export: Through the GUI, you can perform backups of databases (using pg_dump under the hood) and restore from dump files. Similarly, it provides wizards to import or export data to CSV and other formats, which can be easier than crafting the COPY commands manually.
• User Management: You can administer roles and permissions with pgAdmin. Creating new login/group roles, granting privileges on schemas and tables, etc., can be done through dialog windows – making database security configuration more approachable than writing SQL GRANT statements by hand.

Pros:

• First-Class for Postgres: Since it’s built for PostgreSQL specifically, pgAdmin tends to support new Postgres features as they come out (e.g., new data types or index types) and represents Postgres concepts (like tablespaces, compound triggers, etc.) very thoroughly. It’s a one-stop interface for Postgres needs.
• Free & Open Source: It’s completely free, which is expected as part of the Postgres ecosystem. Businesses and individuals can use it without any licensing concerns, and it improves based on community contributions and feedback.
• Full Admin Capabilities: Unlike some general SQL clients that focus mostly on queries, pgAdmin is built with admin tasks in mind. You can manage server configurations, set up streaming replication, inspect locks, and more – tasks that general IDEs might not handle.
• Cross-Platform Web UI: Because it runs as a web application (even the desktop version is essentially a packaged browser), the interface is consistent across OSes. You can also host pgAdmin on a server and access it via browser, which is useful for remote database administration.

Cons:

• Performance and Memory: Running pgAdmin 4 can be heavier than its old desktop predecessor or simpler clients. The web-based architecture means it can sometimes feel slow, and it will consume a chunk of RAM, especially when multiple tabs or large result sets are open.
• Interface Quirks: Some users find the interface less responsive or intuitive compared to native apps. For example, opening a new query tool might be slower than expected, or error messages might appear in separate windows. It’s improved over time, but still not as snappy as a lightweight editor for quick querying.
• Postgres-Only: Similar to MySQL Workbench, the scope is limited to PostgreSQL. If you work with various database systems, you’d need to use pgAdmin for PG and something else for others, which can fragment your workflow.
• Limited Collaboration/Sharing: pgAdmin does not have features to share queries or results with others aside from manually saving and sending files. It’s meant for individual database management tasks rather than collaborative analytics or editing.

Platforms: Windows, macOS, Linux (desktop app), or Web (when deployed on a server). Pricing: Free and open source.

8. Mode Analytics

Mode Analytics is a bit different from the typical SQL IDE – it’s a cloud-based collaborative data analytics platform that combines an SQL editor with visualization and reporting capabilities. Aimed at data analysts and data scientists, Mode provides an online environment where you can query your database (via SQL), then analyze or visualize the results (using built-in charts or even by writing Python/R notebooks), and finally share the findings with your team or stakeholders. Mode is accessible entirely through the browser and connects to your databases (like Redshift, Snowflake, Postgres, etc.) over secure connections. It’s popular among analytics teams because it streamlines the workflow from raw query to final report in one tool, encouraging both collaboration and reproducibility.

Key Features:

• Integrated SQL, Python, and R: In Mode, a typical workflow starts with writing an SQL query in the editor. The results of that query can then be piped into a pandas DataFrame in a Python notebook or an R data frame in an R notebook, all within the same report. This allows for deeper analysis (like statistical analysis or machine learning) after pulling data via SQL.
• Visualization and Reporting: Mode has a built-in visualization builder for turning SQL result sets into charts (bar charts, line charts, maps, etc.). You can create dashboards or interactive reports consisting of one or multiple charts and tables. These reports update automatically when underlying data changes (if scheduled) or when a viewer refreshes them.
• Collaboration & Sharing: Multiple team members can collaborate on a Mode report. You can easily share a report via URL with others in your organization, with fine-grained permissions (viewer, editor). There’s also commenting and annotation features, so teams can discuss the results right in the tool. Version history of reports/queries is maintained as well.
• Database Connections & Schedules: Mode connects to many SQL databases and data warehouses. You manage your connections centrally (with credentials encrypted). Queries can be scheduled to run on a cadence, which is great for nightly reports or periodic updates. The results can even trigger email reports or alerts if needed.
• Knowledge Library: As teams use Mode, they build up a library of analysis (SQL queries, reports, etc.) that can be searched and reused. This helps avoid duplicate work – if someone has already written a query for a certain metric, others can find it and build upon it, fostering a collaborative data culture.

Pros:

• End-to-End Workflow: Mode shines in scenarios where you don’t want just an SQL query, but a presentable analysis. It removes friction by letting you go from data extraction to analysis to visualization in one place. You don’t have to juggle a SQL tool, a separate notebook, and a spreadsheet/charting tool – Mode combines them.
• Great for Teams: The platform is built with teams in mind. Reports and queries can be easily shared, reducing silos. It’s excellent for analytics teams that want to collaborate or for delivering self-service reporting to non-technical users via the published dashboards.
• No Installation & Easy Updates: Being web-based, there’s nothing to install. It’s also database-agnostic on the client side – Mode handles the drivers. You always get the latest features without any upgrades on your end. This also makes it easy to onboard new team members (just create an account and they’re set).
• Extensible with Code: The ability to use Python and R for advanced analysis within Mode means analysts aren’t limited by SQL for complex data manipulation. If something can’t be done in SQL alone, it likely can be done by pulling data into Python/R within Mode, which is a big plus for data science use cases.

Cons:

• Primarily Online: Mode requires an internet connection and access to their cloud. Some companies might have strict data policies that make using a cloud service tricky (though Mode does offer secure on-prem database connections, the interface is still cloud-hosted).
• Cost for Full Features: While Mode offers a free plan (Mode Studio) for individuals or small-scale use, the advanced collaboration features and higher usage limits come with paid plans. These can be pricey for large organizations, which might limit who in the company gets access if budgets are tight.
• SQL Editor is Basic: The SQL editing environment, although functional, is not as feature-rich as desktop IDEs. It has autocomplete for basic SQL syntax and schemas, but it lacks some advanced IDE features like refactoring or debugging. It’s also bound by the web browser capabilities for handling very large queries or results.
• Learning Curve for Advanced Features: Basic usage (writing a query) is straightforward, but leveraging the full power of Mode (with multi-stage analysis, custom visuals, scheduling, etc.) has a learning curve. New users may need training to use Mode effectively as an analytical tool, not just a SQL runner.

Platforms: Web (Cloud service; works on any modern browser). Pricing: Free for basic individual use (Mode Studio); Team/Business plans are paid (pricing based on users and features, often starting in the thousands of USD per year for organizations).

9. Hex

Hex (by Hex Technologies) is another cutting-edge platform in the analytics space – essentially a collaborative data notebook that brings together SQL, Python, and no-code visualization in one place. Think of Hex as a next-gen Jupyter notebook that’s cloud-based, real-time collaborative (multiple people can work in the same notebook simultaneously), and geared toward both data exploration and reporting. Hex allows users to connect to their databases or data warehouses, write SQL queries to pull data, then continue the analysis with Python (or just keep everything in SQL) and output findings as interactive visualizations or apps. Hex notebooks can be shared or embedded, making it possible to use them as internal tools or live reports. For teams that want the flexibility of coding notebooks with the polish of BI tools, Hex strikes a compelling balance.

Key Features:

• Multi-Cell Notebook Environment: In Hex, you create notebooks composed of cells. Cells can be SQL queries, Python code, Markdown documentation, or visualizations. For example, you might have a SQL cell to fetch some data, followed by a Python cell that uses pandas to further manipulate that data, followed by a visualization cell to chart the results.
• Real-Time Collaboration: Hex notebooks are collaborative in a Google Docs-like manner. Team members can edit different cells at the same time, see each other’s changes live, and comment on specific parts of the analysis. This is a big leap over traditional Jupyter notebooks which are typically single-user.
• AI Assist: Hex has integrated AI features to help write code. This includes suggestions or even auto-generation of code (SQL or Python) based on comments or prompts. This can accelerate analysis for users by handling boilerplate code or helping with unfamiliar syntax.
• Interactive Apps & Sharing: One of Hex’s strengths is that once you’ve built an analysis in the notebook, you can easily turn it into an interactive app or dashboard for others. For example, you can expose certain parameters (like a date range or filter criteria) so that non-technical users can adjust and run the analysis via a web interface without altering the code. Notebooks or apps can be shared via URL or embedded, with control over who can view or run them.
• Connections & Integrations: Hex connects to many data sources: SQL databases, data warehouses (Snowflake, BigQuery, etc.), and even APIs. It also integrates with Github for version control of notebooks, and with Slack or email for notifications. This ensures it fits into existing data stack workflows.

Pros:

• Blend of SQL and Coding: Hex doesn’t force you to choose between a SQL editor or a programming notebook – you can use both synergistically. This is great for data teams where some members prefer SQL and others want to use Python for more advanced analysis. Everyone can collaborate in one place.
• Collaborative & Versioned: The real-time editing and built-in version history make it easy for a team to work together and trust the state of the project. It reduces the “stale notebook” problem where one person’s local analysis might get lost or duplicated.
• Production-Ready Outputs: With Hex, your analytical work can directly become a user-facing tool. Instead of rewriting an analysis into a separate dashboard tool, you can just share the Hex app. This drastically shortens the cycle from exploration to delivering insights to stakeholders.
• Modern User Experience: Hex’s interface is modern and thoughtful, with useful touches like auto-complete, documentation hints, and drag-and-drop for reordering cells. It’s in active development, so new conveniences (like the AI assist) are regularly introduced, keeping it on the cutting edge.

Cons:

• Cloud-Hosted: Similar to Mode, Hex is a cloud application. You’ll need to send your queries and data (results) to Hex’s platform. For some companies, data governance or privacy rules might require a careful review or usage of a self-hosted option (Hex does offer a private instance for enterprise, but for small teams it’s multi-tenant cloud).
• Cost and Limits: Hex offers a free tier for small usage, but for full team collaboration and larger compute resources, it’s a paid product. The pricing can add up for larger teams or heavy usage, which might limit adoption to teams that have budget specifically for advanced analytics tools.
• Learning Curve for Non-Coders: While analysts comfortable with notebooks will pick up Hex quickly, some purely SQL-focused users or business users might find the notebook paradigm unfamiliar. They might prefer more straightforward drag-and-drop BI tools unless they invest time in learning Hex.
• Still Maturing: Hex is relatively new. Occasionally, users might run into features that are in beta or need refinement. Compared to very established tools, there might be minor gaps (which are likely to close given Hex’s rapid development pace, but it’s something to be aware of in the present state).

Platforms: Web (Cloud platform, with options for private cloud deployment). Pricing: Free community tier (limited compute and collaboration); paid plans for teams and enterprise with expanded capabilities and resources.

10. Cursor (AI Code Editor)

Cursor is an AI-powered code editor that has gained attention for its ability to act as an “AI pair programmer.” While Cursor is a general code editor (supporting many programming languages), it’s relevant to SQL because it can help generate and complete SQL queries using natural language and context from your codebase. Cursor’s interface is similar to Visual Studio Code and it runs as a desktop application (available for Mac and Windows, with Linux support in development). The key selling point is its AI-driven features: as you write code or queries, Cursor’s AI can predict and suggest the next lines or even entire blocks. For SQL, this means you can describe the data or result you need, and the AI might draft the SQL for you – which you can then refine. It doesn’t connect to databases directly in a GUI manner, but many developers use Cursor alongside database CLI tools or simple scripts to run the SQL that Cursor helps them write.

Key Features:

• AI Autocomplete Everywhere: Cursor’s AI model is always running as you type, offering to complete your code or query. It’s not just basic keyword suggestions; it can suggest multi-line snippets based on context. For example, if you start writing a SELECT statement and mention a table name, it might suggest common column selections or JOIN clauses automatically.
• Natural Language Prompts: You can write a comment or instruction, like "-- find all customers who made a purchase in the last month" and Cursor’s AI can attempt to generate the corresponding SQL for you. It’s like having ChatGPT integrated into your editor, trained to output well-formatted code.
• Multi-Language Support: If your workflow involves more than just SQL – say you’re writing a Python script that connects to a database – Cursor can assist with both the SQL part and the Python part. It understands context across different file types in your project, which is helpful in applications that embed SQL in code.
• Chat Interface: Aside from inline suggestions, Cursor includes a chat sidebar where you can ask questions or instructions about your code (or any code). You could paste an SQL query and ask the AI to explain it or optimize it, and it will provide answers or new code suggestions.
• Extensibility and Familiarity: Cursor allows you to import VS Code extensions, themes, and keybindings, meaning you can set it up just like your VS Code environment. This makes it a fairly comfortable switch for those used to traditional code editors, just with added AI capabilities.

Pros:

• AI Boosts Productivity: For SQL, this means you can draft queries faster, especially ones with repetitive patterns or complex logic, by leveraging AI suggestions. It’s like having an assistant that writes boilerplate or looks up syntax for you. This can be a huge time-saver when you vaguely know what you want to do but don’t recall the exact SQL syntax or function.
• Works with Existing Workflow: Cursor doesn’t force a new workflow – you can use it as a coding environment just as you would VS Code or others. This means you can still run your SQL by connecting to the database through a terminal or script, but benefit from Cursor’s writing assistance in composing the queries.
• Multi-Purpose Tool: It’s not limited to SQL. If your job involves writing application code plus occasional SQL, Cursor can serve both needs. You don’t have to leave your editor to get help with an SQL query, which can keep you “in the zone.”
• Constant Improvement: As an AI-centric tool, Cursor is continuously evolving with improvements to its models and features. It has a community around it and is often integrating the latest in AI advancements (like new large language model updates) to keep the suggestions cutting-edge.

Cons:

• Not a Database GUI: It’s important to note that Cursor won’t show you tables or run queries for you in a visual manner. It’s primarily an editor. So you might still need to use another tool to actually execute the queries and see results (unless you’re embedding the query in code and running that code). This means it complements rather than replaces a traditional SQL client.
• Dependent on AI Accuracy: While the AI is powerful, it isn’t foolproof. It may generate incorrect SQL or suboptimal approaches. You need enough SQL knowledge to validate and correct the AI’s output. Relying on it blindly could lead to mistakes. Think of it as a helper, not an authoritative source.
• Privacy/Compliance: Using an AI tool may raise concerns if you’re working with sensitive code or queries. Cursor has privacy modes, but organizations may need to vet how code is being sent to AI servers (though some of Cursor’s functionality might run locally or with protected models if configured). Always a consideration with AI developer tools.
• Limited Niche Use for SQL-Only Folks: If someone is strictly looking for a SQL IDE and doesn’t do general programming, adopting Cursor just for SQL writing might be overkill. It shines best when you’re intermixing SQL with other code or want AI help across your development tasks, not solely as a standalone query editor.

Platforms: macOS, Windows (Linux support expected). Pricing: Free version available (with generous AI usage limits); Pro subscription offers more advanced AI models (like GPT-4) and higher usage quotas for heavy users.

11. Vim (with CLI Tools)

For power users who live in the terminal, Vim (a command-line text editor) can double as an SQL editor. Out of the box, Vim provides syntax highlighting for SQL and can be used to compose queries in a very lightweight environment. While Vim itself doesn’t connect to databases or execute queries, it can be paired with command-line database clients (such as psql for PostgreSQL or mysql for MySQL) and various plugins to create a quite capable SQL editing experience. Some developers prefer this approach because it avoids heavy GUI tools and fits into their coding workflows (especially if they are SSHing into servers or working on remote systems). Using Vim for SQL is definitely a more specialized use-case, but it’s a testament to Vim’s flexibility and the preferences of certain engineers.

Key Features (with proper configuration):

• Lightweight Editing: Vim is extremely fast and works in any terminal. You can open a .sql file or just start writing an SQL query without worrying about project setup. The editor will highlight SQL keywords and can be configured to indent/format SQL for readability.
• Plugins for DB Interaction: There are Vim plugins like vim-dadbod or vim-dadbod-ui that allow you to execute SQL queries directly from Vim and see the results. These plugins let you configure database connections and then run a query in your Vim buffer, returning the results in another buffer or pane.
• Macros and Automation: Because it’s Vim, you can record macros or use powerful find/replace and multi-cursor techniques to manipulate SQL text quickly. Repetitive tasks in editing SQL (like adding prefixes to a bunch of lines) can be done in seconds with the right commands.
• Always Available: Vim (or its cousin Vi) is present on virtually all Unix-like systems by default. If you’re logged into a server and need to write or tweak a quick SQL query (perhaps to run it with a CLI tool), Vim is reliably there, no GUI or installation needed. This makes it valuable for quick edits in remote environments.
• Customization: Users can configure Vim to their heart’s content. You can set up custom syntax rules, use auto-completion plugins (for instance, to complete table or column names if you feed them from a schema file), and generally adapt the editor to suit your SQL coding style.

Pros:

• Efficiency for Experts: For those who are proficient in Vim, editing anything (including SQL) can be extremely efficient. All navigation and editing can be done via keyboard at lightning speed once muscle memory is built, often faster than using a mouse-driven GUI.
• Minimal Resource Usage: Vim is tiny compared to an IDE – it will run on systems with very low memory and CPU. It’s ideal if you’re working over SSH on a remote database server or if you don’t want to launch a big application just to run a quick query.
• Integrated with Terminal Tools: Because it’s in the terminal, it’s easy to incorporate into scripts or a terminal-centric workflow. You can write a query in Vim, then immediately run it by switching to a command-line (or using a Vim plugin). It's seamless if you’re comfortable in that environment.
• Free and Always Accessible: Vim is open source and comes pre-installed on many systems. There’s no barrier to use it. Plus, once you know Vim, that knowledge transfers to editing any text-based file (not just SQL) on any system, which some see as a valuable skill.

Cons:

• Steep Learning Curve: Vim is infamous for its learning curve. It’s not intuitive for new users (even quitting Vim without guidance can be challenging for a first-timer). Mastery requires significant time investment, which is not worthwhile if you only occasionally edit SQL.
• No Visual Schema Browsing: Unlike GUI clients that show you a list of tables and let you click to see data, with Vim you need to know what you want to query ahead of time. There’s no built-in schema explorer or data viewer. You’d have to query the information schema or use external docs to reference table/column names.
• Setup for DB Interaction: To run queries from Vim, you’ll likely need to install and configure plugins and ensure command-line clients for the databases are available. This setup can be non-trivial. Without that, Vim alone is just an editor and you’d copy-paste queries to a database CLI to execute.
• Not Newbie-Friendly: For someone who isn’t already comfortable with command-line editors, recommending Vim as an SQL editor would probably be counterproductive. The productivity gains are only realized by advanced users, so it’s not a general solution for most teams or individuals who primarily want ease of use.

Platforms: Windows (via gVim or WSL), macOS, Linux, BSD – anywhere a terminal exists. Pricing: Free and open source.

12. Postico (Postgres) & Sequel Ace (MySQL) [macOS]

Mac users have a couple of excellent native SQL clients tailored to specific databases: Postico for PostgreSQL and Sequel Ace for MySQL/MariaDB. These tools are distinct, but we’ll mention them together as they share a similar philosophy – providing a lightweight, user-friendly Mac-native experience for their respective database systems. Both are highly regarded in the Mac developer community for being simple, fast, and convenient for everyday tasks, albeit each focuses on a single database type.

Postico is a macOS application for PostgreSQL databases (including compatible systems like Amazon Redshift or CockroachDB). It offers a straightforward interface to run queries, explore tables, and edit data. Postico emerged as the successor to the older “PgAdmin III” on Mac, with a much more modern UI. Developers who want a quick way to connect to a Postgres database, browse schema, and execute queries appreciate Postico’s no-frills approach. It supports features like multiple query tabs, prepared statement handling, and copying results to CSV.

Sequel Ace is the community-driven successor to the famed Sequel Pro (which was a long-time favorite for MySQL on Mac). Sequel Ace continues that legacy, providing a free and open-source GUI for MySQL and MariaDB. It’s great for managing local databases (like your development MySQL instance or testing environment) and even connecting to remote MySQL servers. The app allows you to quickly view tables, run queries, and perform table operations (add/drop columns, indexes, etc.) through a native Mac interface. It also supports SSH tunneling for secure remote access, making it handy for connecting to a MySQL database on a server without exposing it directly.

Key Features (Postico):

• Elegant table browsing: Click on a table to view rows, with the ability to sort and filter results quickly in the UI.
• Simple query editor: Supports multiple tabs and retains your query history. It has basic autocomplete for SQL keywords and recently used identifiers.
• Import/export: You can import CSV files into tables or export query results and tables to CSV/JSON conveniently.
• Server compatibility: Works with PostgreSQL, and also tested with Amazon Redshift and other Postgres derivatives. It handles the slight differences in these systems fairly well.
• Native feel: Uses Mac standards for things like keychain storage of passwords, drag-and-drop, etc., giving a smooth user experience on macOS.

Key Features (Sequel Ace):

• Quick connect & management: Save favorite connections (including via SSH). Once connected, you can see your schemas, tables, views, routines, etc. in a sidebar.
• Query and table views: Has a full SQL query editor with syntax highlighting. Also, a table view where you can edit cells directly (good for small data tweaks or inserts without writing SQL).
• Export/Import: Dump tables or results to SQL files, CSV, or even directly to other databases. Import SQL scripts or CSV data easily.
• Multiple query windows: Open several windows or tabs to run different queries in parallel, which is useful when comparing results or copying data between databases.
• Open source and improving: Since it’s open source, it’s continuously updated by contributors. It supports the latest macOS releases and Apple Silicon natively.

Pros (Postico & Sequel Ace):

• Mac-Optimized: Both tools take advantage of Mac UI conventions, making them feel more responsive and integrated than some cross-platform clients. They are great for Mac users who want a native look and feel.
• Easy to Learn: The interfaces are straightforward. There aren’t an overwhelming number of buttons or panels. A beginner can get up and running – connect to a database, run a SELECT query, or edit a row – with minimal instruction.
• Focused and Stable: By focusing on one database system, each tool avoids the complexity of multi-database support. This often leads to fewer bugs and quirks. They excel at the intended use (Postico for Postgres, Sequel Ace for MySQL) and don’t burden the user with irrelevant options.
• Lightweight: They launch quickly and perform well for most typical tasks. For example, Sequel Ace is known to be faster and more reliable on Mac than the cross-platform MySQL Workbench for browsing MySQL databases.
• Sequel Ace is Free: Being open source, Sequel Ace costs nothing, which is fantastic for a tool of its capability. Postico offers a free trial and a very reasonable one-time purchase for continued use, so both are accessible.

Cons (Postico & Sequel Ace):

• Mac Only: The obvious downside is these solutions are not available on Windows or Linux. Teams that are multi-OS can’t standardize on these, and an individual who switches to a different OS will need to find a new tool.
• One-Database Limitation: If your work involves multiple database types, you’ll need to use these in conjunction with other clients. For example, you might use Postico for Postgres but still need a different tool for MySQL or vice versa. This can be less convenient than a one-size-fits-all tool like DBeaver if you often juggle many DB types.
• Fewer Advanced Features: These apps are lean by design, which means they might lack some advanced functionality. For instance, Postico doesn’t have a built-in SQL explain plan viewer – you’d have to run EXPLAIN manually. Sequel Ace might not have as advanced performance monitoring or debugging tools as enterprise-grade clients. They cover everyday use cases well, but edge-case needs may require a supplemental tool or manual SQL/script work.
• Development Pace: While Sequel Ace is active, it’s community-driven and can have slower development at times than a commercial product with a full team. Postico is primarily developed by a small team (or individual developer), so major updates or new features come at the developer’s pace. This is usually fine, but it means you might not see brand-new features as quickly as in larger projects.

Platforms: macOS only. Pricing: Postico – free trial then paid (around $50 one-time for Postico 1, with Postico 2 in beta at similar pricing); Sequel Ace – free (open source).

Choosing the Right SQL Editor

The “best” SQL editor or IDE ultimately depends on your specific needs and workflow. If you prioritize collaboration and modern features, a tool like Galaxy (with its real-time teamwork and AI assistance) could dramatically improve your productivity. For those deeply involved in software development and managing complex schemas, an advanced IDE like DataGrip or a versatile client like DBeaver may be more suitable. Analysts focusing on data visualization and sharing insights might gravitate toward platforms like Mode or Hex, which blend SQL with analysis and reporting. Meanwhile, many developers stick to what’s comfortable – some love the speed of TablePlus or Beekeeper Studio for everyday querying, and a few even swear by terminal-based solutions like Vim for maximum efficiency.

Importantly, many of these tools can complement each other. You might use a collaborative cloud tool for some scenarios and a fast local client for others. Most offer free versions or trials, so it’s worth trying out a couple to see which interface and feature set you prefer. The good news is that in 2025, there is no shortage of excellent SQL editors – whether you need a free SQL client for basic tasks or a cutting-edge IDE for enterprise database development, the options above have you covered. Happy querying!