Implementing faceted search with Django and PostgreSQL

Re:Implementing faceted search with Django and PostgreSQL by simonw on Thursday October 05, 2017 @02:20PM (#15411356)

Elasticsearch is massively more powerful and flexible.

The way I'm doing aggregation counts on top of PostgreSQL is very unlikely to scale to millions of documents. Elasticsearch pretty much acts as a real-time, horizontally scalable map/reduce engine so expensive aggregations get executed on multiple shards and the results are gathered back together.

You may find my talk from DjangoCon this year interesting: https://speakerdeck.com/simon/the-denormalized-query-engine-... / https://www.youtube.com/watch?v=NzcvewgqYog

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Re:Implementing faceted search with Django and PostgreSQL by StavrosK on Thursday October 05, 2017 @09:34PM (#15413842)

What type of data is ES good for? It's more than documents and full-text search, if I'm not mistaken, correct?

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Re:Implementing faceted search with Django and PostgreSQL by bebop on Thursday October 05, 2017 @10:51PM (#15414105)

I have used it as a general data store, where I can accept eventual consistency. It is a very good distributed db if you are ok with the trade offs it imposes, mostly non-atomic commits to your cluster.

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Re:Implementing faceted search with Django and PostgreSQL by othersideofcoin on Thursday October 05, 2017 @11:04PM (#15414148)

It also excels at storing logs for later aggregation and analysis.

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Re:Implementing faceted search with Django and PostgreSQL by StavrosK on Friday October 06, 2017 @06:40AM (#15415718)

Thank you, I was specifically wondering how good it is at data ingestion for warehousing. Good to know that's one of its strengths.

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