• v1.0.0

Local installations are essential for testing, development, and offline work. Installing Data Hub locally offers the ability to explore its features, troubleshoot, and test integrations without relying on cloud environments. In this guide, we’ll walk you through several methods for installing Data Hub, including Docker-based and programming language-specific installations, with examples for each.

What is Data Hub?

Data Hub is an open-source metadata platform that provides a comprehensive solution for managing, discovering, and sharing data across the organization. By offering data lineage, governance, and visualization tools, it helps organizations manage their data effectively. Installing Data Hub locally allows developers and data engineers to explore its functionalities in a controlled environment.

1. Docker-Based Installation

Docker is one of the most popular methods for containerized installation, providing a straightforward way to set up Data Hub in an isolated environment. Using Docker allows you to quickly deploy Data Hub without worrying about complex dependencies or environment configurations.

Steps to Install Data Hub Using Docker

Install Docker: If you haven’t installed Docker yet, start by downloading and installing Docker Desktop from Docker’s official website.

Clone the Data Hub Repository: Open your terminal and clone the Data Hub repository from GitHub:

git clone https://github.com/datahub-project/datahub.git

Navigate to the Data Hub Directory: Change your directory to the cloned repository:

cd datahub

Run Docker Compose: Data Hub uses Docker Compose to orchestrate multiple containers (like Kafka, Elasticsearch, and more). To start the containers, run the following command:

docker-compose up

This will download the necessary Docker images and start the required services. Once the setup is complete, you can access the Data Hub UI at http://localhost:9002.

Stop Docker Containers: To stop the containers, use:

docker-compose down

Docker-based installation is simple and ideal for quick testing or development setups.

2. Python (pip) Installation

If you prefer to install Data Hub using Python’s package manager, pip, you can follow these steps. Note that Python installations require the appropriate Python version (typically Python 3.x).

Steps to Install Data Hub Using pip

Ensure You Have Python Installed: First, check that Python is installed by running:

python --version

If not, you can install it from the official Python website.

Create a Virtual Environment (optional but recommended): It’s a good practice to use a virtual environment to avoid dependency conflicts. Create one with:

python -m venv datahub-env

Activate it by running:

On Windows:

datahub-env\Scripts\activate

On macOS/Linux:

source datahub-env/bin/activate

Install Data Hub: Run the following command to install Data Hub via pip:

pip install datahub

Verify Installation: After installation, verify that Data Hub is correctly installed by running:

datahub --help

3. Node.js (npm) Installation

For those who prefer to use Node.js for the installation, the process is relatively straightforward. You can install Data Hub’s Node.js components using npm, Node’s package manager.

Steps to Install Data Hub Using npm

Ensure You Have Node.js and npm Installed: Check your Node.js installation by running:

node --version

If you don’t have Node.js installed, download it from nodejs.org.

Install Data Hub Using npm: Once Node.js is installed, you can use npm to install Data Hub’s CLI tool:

npm install -g datahub-cli

Verify Installation: After installation, verify it by running:

datahub --help

4. Java (Maven/Gradle) Installation

Data Hub’s Java components can be installed via Maven or Gradle, popular build automation tools for Java applications.

Steps to Install Data Hub Using Maven

Ensure You Have Java and Maven Installed: First, check your Java installation:

java -version

To install Maven, follow the instructions on the official website.

Clone the Repository: Clone the Data Hub repository from GitHub:

git clone https://github.com/datahub-project/datahub.git

Build the Project: Navigate to the Data Hub directory and run the following Maven command to build the project:

mvn clean install

Run Data Hub: After building the project, you can run Data Hub using Maven:

mvn exec:java

Alternatively, you can package Data Hub as a JAR file and run it using:

java -jar target/datahub-<version>.jar

Steps to Install Data Hub Using Gradle

Ensure You Have Java and Gradle Installed: Check your Java installation and install Gradle by following instructions on the Gradle website.

Clone the Repository: Clone the Data Hub repository:

git clone https://github.com/datahub-project/datahub.git

Build the Project: Navigate to the Data Hub directory and build it using Gradle:

gradle build

Run Data Hub: After building the project, you can run Data Hub:

gradle run

Managing and Verifying Your Installation

After installation, you may want to verify that everything is set up correctly. Here are some tips for managing and checking your installation:

Check the Data Hub UI: If using Docker, you can access the Data Hub UI at http://localhost:9002. Ensure that all services are running as expected.

Check Services: For Docker installations, verify that all containers are running by executing:

docker ps

View Logs: For troubleshooting, check the logs for any errors. If you’re using Docker, you can access logs with:

docker-compose logs

Test Functionality: Run basic Data Hub commands to ensure the installation works:

datahub metadata status

Conclusion

Installing Data Hub locally allows you to test its features, experiment with its APIs, and explore metadata management tools in an isolated environment. Whether using Docker, Python, Node.js, or Java, the installation process is straightforward and adaptable to various development workflows. By following the provided instructions, you can quickly get Data Hub up and running on your local machine.

Last Releases

• v1.0.0March 17, 2025
  DataHub v1.0.0 Release Highlights DataHub v1.0.0 is packed with exciting updates, including: A completely redesigned user experience focused on simplified navigation and a visually stunning interface. Unified support for Data… Read more: v1.0.0
• v0.15.0.1January 21, 2025
  Full Changelog: v0.15.0…v0.15.0.1   Source: https://github.com/datahub-project/datahub/releases/tag/v0.15.0.1
• V0.15.0January 17, 2025
  DataHub v0.15.0 Release Notes User Experience Structured Properties Added comprehensive support for managing structured properties, including creation, editing, deletion, and display preferences. Introduced timestamps for tracking creation and modification. [#12100,… Read more: V0.15.0