DataHub

What it is

DataHub is LinkedIn's open-source platform designed to help organizations discover and understand their data assets by providing a centralized view of all metadata. It enables users to search, browse, and manage metadata across various systems, improving data governance and collaboration within teams.

DataHub stands out as an open-source solution for comprehensive metadata management, offering a unified view of data assets across various systems without the need for cloud services.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Steep learning curve for non-Java developers

   DataHub's primary language is Java, and its extensive use of Java-specific patterns can be challenging for developers unfamiliar with the language.

2. 02

   Limited documentation and community support

   The official documentation lacks detailed examples and troubleshooting guides. Community forums and Stack Overflow have limited activity specific to DataHub issues.

3. 03

   Complex setup and configuration process

   Setting up DataHub requires significant configuration, including integrating with various data sources and setting up metadata ingestion workflows, which can be time-consuming and error-prone.

4. 04

   Performance issues at scale

   As the volume of metadata increases, DataHub may experience performance degradation due to its current architecture and indexing mechanisms, leading to slower search and discovery times.

What it does well

• Centralized metadata management across multiple systems.

• Search and discovery of data assets within an organization.

• Integration with various data sources for comprehensive metadata collection.

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.