Mathesar screenshot

Mathesar

Updated: 23 May 2025
4144 Stars

An intuitive spreadsheet-like interface that lets users of all technical skill levels view, edit, query, and collaborate on Postgres data directly—100% open source and self hosted, with native Postgres access control.

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Overview:

Mathesar is an open-source tool that offers a user-friendly interface for interacting with PostgreSQL databases. Users can work with data, build models, enter data, and generate reports without needing technical expertise. Mathesar allows users to self-host their installation, ensuring ownership, privacy, and control over their data.

Features:

  • Built on Postgres: Connect to existing Postgres databases or set up a new one.
  • Data Models: Easily create and update Postgres schemas and tables.
  • Data Entry: Utilize a spreadsheet-like interface for viewing, creating, updating, and deleting table records.
  • Filter, Sort, and Group: Quickly manipulate data in various ways.
  • Query Builder: Build queries using the Data Explorer without SQL knowledge.
  • Schema Migrations: Transfer columns between tables with ease.
  • Postgres Features: Utilizes Postgres schemas, keys, constraints, and data types.
  • Custom Data Types: Includes custom data types for emails and URLs.
  • Basic Access Control: Offers roles such as Viewer, Editor, and Manager for data access control.

Installation:

  1. Clone the Mathesar repository from GitHub.
  2. Install the required dependencies by running pip install -r requirements.txt.
  3. Configure your PostgreSQL database settings in the config.py file.
  4. Run the Mathesar server using python app.py.
  5. Access Mathesar through your web browser at the specified address.

Summary:

Mathesar is a versatile tool that simplifies working with PostgreSQL databases, enabling users to manage data, create models, and generate reports effortlessly through its intuitive interface. Self-hosting provides users with complete control and privacy over their data, making Mathesar a valuable asset for individuals and teams looking to collaborate on data projects without the need for extensive technical knowledge.