Amundsen Demo: Explore Amundsen in a Pre-configured Sandbox Environment

Updated August 30th, 2023
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Amundsen Data Catalog Demo

Here’s a hosted demo environment that should give you a fair sense of the Lyft Amundsen data catalog platform.

For a quick catch-up, also explore this video and others in the channel which has Amundsen data catalog demos, community meetings, conference presentations etc.

What is Amundsen Data Catalog?

Amundsen is an open source data discovery platform and metadata engine that was developed by the Lyft Engineering team. Amundsen data catalog was built to improve the productivity and efficiency of data practitioners at Lyft.

It was open-sourced in October 2019, a year after launching in production. Amundsen since then has enjoyed a buzzing community of users, who have expanded it to build their data catalog on top of it.

The main capabilities of Amundsen include:

  • Easy data discovery
  • Automated and curated metadata - powering use cases
  • Ability to share knowledge & context with coworkers
  • Enabling learning from data usage

Are you evaluating Amundsen Data Catalog for querying, lineage, profiling, and other specific use cases? Trying the open source data catalog tool hands-on is an important step of this evaluation process. What are the other crucial steps that you must undertake while evaluating a data catalog? Get hold of this check list to stay on track!

Also interested in other open source data catalogs? Check out this compilation of the most popular open source data catalog tools to ensure you aren’t missing out on any of them.

If you are a data consumer or producer and are looking to champion your organization to optimally utilize the value of your modern data stack — while weighing your build vs buy options — it’s worth taking a look at off-the-shelf alternatives like Atlan — Home to the modern data teams.

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"It would take six or seven people up to two years to build what Atlan gave us out of the box. We needed a solution on day zero, not in a year or two."

Akash Deep Verma
Akash Deep Verma

Director of Data Engineering

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Build vs Buy: Delhivery’s Learnings from Implementing a Data Catalog

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