Conclusions
Amundsen is a good contender, but ultimately relies on Atlas for good Hive integration, and that would complicate our deployment quite a bit.
Pros
- simple architecture of 3 flask services all in python (as opposed to Datahub using java and python)
- ingestion architecture is simple: python scripts or airflow dags that make http api requests
- "social" ui features, like frequent users and owners
- loose coupling means you can use a relational database as the data store rather than neo4j (https://github.com/amundsen-io/amundsenrds)
Cons
- seems like the community is losing steam: https://github.com/amundsen-io/amundsen#blog-posts-and-interviews has a flurry of events in 2019/2020 but nothing in 2021
- only supports polling for data updates, unless we also deploy atlas. Push ingest api is on their roadmap
- documentation is somewhat lacking; few ingestion examples, and broken links in docs
- some dependencies are getting out of date: elasticsearch version 6 (v7 was released 2019), nodejs version 12 (v13 was released 2019)
Run
- (from T300756#7683747)
- Tunnel with ssh -N -L 5000:localhost:5000 stat1008.eqiad.wmnet
- browse http://localhost:5000
Steps to Reproduce Installation
- ElasticSearch (we'll use OpenSearch here as well)
- Neo4j with some trouble setting up SSL: T300756#7677142
- Configure and launch all the services as mentioned in documentation and T300756#7673715
Ingestion
- Ingest Hive Metastore: T300756#7683747 (second half of that comment)
- Ingest Druid: T300756#7683858
(see slack thread)


