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angrycaptain19/amundsen

Analysis updated 2026-07-18 · repo last pushed 2022-01-15

Audience · dataComplexity · 4/5Dormant

TLDR

Amundsen is a search engine for company data, it helps analysts and engineers find the right tables, dashboards, and datasets across their warehouse in seconds.

Mindmap

mindmap
  root((repo))
    What it does
      Search for data
      Ranks by usage
      Shows table details
    Tech stack
      Elasticsearch
      Neo4j
      Apache Airflow
    Use cases
      Find the right table
      Explore dashboards
      Track data usage
    Audience
      Data analysts
      Data engineers
      Data scientists

Code map

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What do people build with it?

USE CASE 1

Search across a company's tables, dashboards, and datasets like using Google for data.

USE CASE 2

Find which tables are most used and by whom before building on top of them.

USE CASE 3

See column names, descriptions, and sample statistics for a dataset before using it.

USE CASE 4

Automatically refresh metadata from a data warehouse on a schedule using Airflow.

What is it built with?

ElasticsearchNeo4jApache AirflowPython

How does it compare?

angrycaptain19/amundsen0verflowme/alarm-clock0verflowme/seclists
Language—CSS—
Last pushed2022-01-152022-10-032020-05-03
MaintenanceDormantDormantDormant
Setup difficulty—easyeasy
Complexity4/52/51/5
Audiencedatavibe coderops devops

Figures from each repo's GitHub metadata at analysis time.

In plain English

Amundsen is a search engine for data. Just like Google helps you find web pages, Amundsen helps data analysts, scientists, and engineers find the specific tables, dashboards, and datasets they need within their company's data warehouse or lake. It solves a real pain point: when you're working with data, you often don't know where the table you need lives, what columns it contains, or whether anyone else is using it. Amundsen finds that information for you in seconds. The way it works is straightforward. First, the system indexes all your company's data resources, tables from databases like Redshift, BigQuery, Snowflake, and many others, plus dashboards from tools like Tableau or Superset. It learns which tables are used most frequently and by whom. Then when you search, it ranks results the same way Google does: highly-used tables appear higher in the results than rarely-touched ones. You see not just the table name, but details like column names, descriptions, data types, sample statistics, and who last modified it. There's also a web interface where you can browse and explore. The project is built from separate but connected pieces. There's a frontend (a web interface), a search service (powered by Elasticsearch), a metadata service (using databases like Neo4j or Apache Atlas), and a data ingestion tool that pulls information from your existing systems. You can set it up to automatically refresh metadata from your warehouse on a schedule, often using Apache Airflow. This means Amundsen stays in sync with your actual data as it changes. Companies like Lyft, Square, and Edmunds use Amundsen to solve the "data discovery" problem at scale. A data analyst who wants to find customer transaction tables doesn't have to email the data team or dig through documentation anymore, they just search. It also helps with governance: by tracking who uses what data, teams can better understand dependencies and manage data quality. The tool supports most major database systems and works whether your data lives in the cloud or on-premises.

Copy-paste prompts

Prompt 1
Help me set up Amundsen's metadata service and search service so I can index my company's data warehouse.
Prompt 2
Show me how to configure Amundsen's data ingestion tool to pull table metadata from BigQuery.
Prompt 3
Explain how Amundsen ranks search results so frequently used tables appear first.
Prompt 4
Walk me through scheduling Amundsen's metadata refresh with Apache Airflow so it stays in sync with our warehouse.

Frequently asked questions

What is amundsen?

Amundsen is a search engine for company data, it helps analysts and engineers find the right tables, dashboards, and datasets across their warehouse in seconds.

Is amundsen actively maintained?

Dormant — no commits in 2+ years (last push 2022-01-15).

Who is amundsen for?

Mainly data.

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