PostgreSQL for Visual Studio Code vs TablePlus

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PostgreSQL for Visual Studio Code

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TablePlus

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PostgreSQL for Visual Studio Code vs TablePlus: What are the differences?

  1. 1. Language Support: PostgreSQL for Visual Studio Code provides full support for SQL language, allowing users to write, modify, and execute SQL queries within the Visual Studio Code editor. On the other hand, TablePlus offers support for multiple languages in addition to SQL, such as MySQL, SQLite, and MongoDB, making it a more versatile tool for working with different database systems.

  2. 2. Connection Management: PostgreSQL for Visual Studio Code offers a built-in connection manager that allows users to easily establish and manage connections to PostgreSQL databases. It provides features like saving connection credentials, connecting to multiple databases simultaneously, and quickly switching between different database connections. TablePlus also offers connection management capabilities, but it supports a wider range of database systems, allowing users to manage connections to different types of databases from a single interface.

  3. 3. Query Execution: PostgreSQL for Visual Studio Code provides a dedicated SQL query execution tool that allows users to execute SQL queries and view the results directly within the editor. It supports features like query parameterization, result set pagination, and result set exporting to CSV or JSON formats. TablePlus also offers a similar query execution feature, but it provides additional options like query history tracking, query formatting, and syntax highlighting for various SQL dialects.

  4. 4. Schema Design: PostgreSQL for Visual Studio Code includes a schema designer tool that enables users to visually design, edit, and manage database schemas. It offers features like table creation, column manipulation, constraint management, and relationship creation between tables. TablePlus, on the other hand, does not have a built-in schema designer tool, focusing more on providing a streamlined interface for query execution and data exploration.

  5. 5. Visual Data Exploration: PostgreSQL for Visual Studio Code offers a data explorer tool that allows users to browse and query database tables, views, and functions in a visual and intuitive manner. It provides features like filtering, sorting, and grouping of data, as well as the ability to execute ad-hoc queries against the selected data. TablePlus also includes a data explorer feature, but it provides additional options like data editing, importing/exporting data, and generating CRUD (Create, Read, Update, Delete) statements.

  6. 6. Extension Ecosystem: PostgreSQL for Visual Studio Code leverages the extensive extension ecosystem of Visual Studio Code, allowing users to enhance the functionality of the tool through various extensions. These extensions can provide additional features like database migration, code formatting, syntax highlighting, and integration with other development tools. TablePlus does not have a dedicated extension ecosystem but offers a wide range of built-in features and customization options to cater to different user needs.

In Summary, PostgreSQL for Visual Studio Code and TablePlus differ primarily in terms of language support, connection management capabilities, query execution features, schema design tools, visual data exploration options, and extension ecosystems. While PostgreSQL for Visual Studio Code focuses on providing a comprehensive SQL development experience within the Visual Studio Code environment, TablePlus offers a more versatile tool for working with multiple database systems.

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Pros of PostgreSQL for Visual Studio Code
Pros of TablePlus
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    • 5
      Great tool, sleek UI, run fast and secure connections
    • 3
      Free
    • 2
      Perfect for develop use
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      Security

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      What are some alternatives to PostgreSQL for Visual Studio Code and TablePlus?
      PostgreSQL
      PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
      Slick
      It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred.
      Spring Data
      It makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. This is an umbrella project which contains many subprojects that are specific to a given database.
      Dataform
      Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.
      DB
      With DB you can very easily save, restore, and archive snapshots of your database from the command line. It supports connecting to different database servers (for example a local development server and a staging or production server) and allows you to load a database dump from one environment into another environment.
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