doc22940 / datahub-1

A Generalized Metadata Search & Discovery Tool

DataHub: A Generalized Metadata Search & Discovery Tool

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Quickstart | Documentation | Features | Roadmap | Adoption | FAQ | Town Hall

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📣 Next DataHub town hall meeting on November 6th, 9am-10am PDT (convert to your local time)

• Signup sheet & questions
• VC link (we're using zoom!): https://linkedin.zoom.us/j/4698262890
• Meeting details & past recordings

✨ Latest Update:

• Check out the latest DataHub Podcast @ Data Engineering Podcast.
• We've released v0.6.0. You can find release notes here
• We're on Slack now! Ask questions and keep up with the latest announcements.

Introduction

DataHub is LinkedIn's generalized metadata search & discovery tool. To learn more about DataHub, read our LinkedIn Engineering blog post, check out our Strata presentation and watch our Crunch Conference Talk. You should also visit DataHub Architecture to get a better understanding of how DataHub is implemented and DataHub Onboarding Guide to understand how to extend DataHub for your own use cases.

This repository contains the complete source code for both DataHub's frontend & backend. You can also read about how we sync the changes between our internal fork and GitHub.

Quickstart

Please follow the DataHub Quickstart Guide to get a copy of DataHub up & running locally using Docker. As the guide assumes some basic knowledge of Docker, we'd recommend you to go through the "Hello World" example of A Docker Tutorial for Beginners if Docker is completely foreign to you.

Documentation

• DataHub Developer's Guide
• DataHub Architecture
• DataHub Onboarding Guide
• Docker Images
• Frontend
• Web App
• Generalized Metadata Service
• Metadata Ingestion
• Metadata Processing Jobs

Releases

See Releases page for more details. We follow the SemVer Specification when versioning the releases and adopt the Keep a Changelog convention for the changelog format.

FAQs

Frequently Asked Questions about DataHub can be found here.

Features & Roadmap

Check out DataHub's Features & Roadmap.

Contributing

We welcome contributions from the community. Please refer to our Contributing Guidelines for more details. We also have a contrib directory for incubating experimental features.

Community

Join our slack workspace for discussions and important announcements. You can also find out more about our upcoming town hall meetings and view past recordings.

Adoption

Here are the companies that have officially adopted DataHub. Please feel free to add yours to the list if we missed it.

• Expedia Group
• Experius
• Grofers
• LinkedIn
• Saxo Bank
• Shanghai HuaRui Bank
• TypeForm
• Valassis

Here is a list of companies that are currently building POC or seriously evaluating DataHub.

• Amadeus
• Bizzy Group
• Booking.com
• Experian
• FlixBus
• Geotab
• Kindred Group
• Instructure
• Inventec
• Microsoft
• Morgan Stanley
• Orange Telecom
• REEF Technology
• SpotHero
• Sysco AS
• ThoughtWorks
• University of Phoenix
• Vectice
• Viasat
• Wolt
• Weee!

Select Articles & Talks

• DataHub: A Generalized Metadata Search & Discovery Tool
• Open sourcing DataHub: LinkedIn’s metadata search and discovery platform
• DataHub: Powering LinkedIn's Metadata @ Budapest Data Forum 2020
• Metadata Management And Integration At LinkedIn With DataHub @ Data Engineering Podcast
• The evolution of metadata: LinkedIn’s story @ Strata Data Conference 2019
• Journey of metadata at LinkedIn @ Crunch Data Conference 2019
• DataHub Journey with Expedia Group
• Saxo Bank's Data Workbench
• Data Discoverability at SpotHero
• Data Catalogue — Knowing your data
• LinkedIn DataHub Application Architecture Quick Understanding
• LinkIn Datahub Metadata Ingestion Scripts Unofficical Guide
• A Dive Into Metadata Hubs
• 25 Hot New Data Tools and What They DON’T Do
• Emerging Architectures for Modern Data Infrastructure

See the full list here.