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THE VIDEO SHELF · postgres analytics architecture

Breakout Session Presented by Dan Robinson of Heap at PGConf Silicon Valley 2015

Dan Robinson, then CTO of Heap, explains how Heap runs its product analytics backend on PostgreSQL and CitusDB. It covers conversion funnels, retention and cohort queries across tens of billions of events and 50 TB of data, plus Postgres and Kafka together and the indexing strategy.

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Why HN readers recommended it

HN commenters point to it as a first-hand overview of Heap's Postgres/Citus architecture and its distinctive indexing approach.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Citus Data
Topic
postgres analytics architecture
Format
talk
Level
advanced
HN recommenders in dataset
4
HN mentions in dataset
8
Recommendation years in dataset
2016–2020

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • I was just watching this[0] excellent talk from one of the Heap Analytics engineers on their use of CitusDB + Postgres to do event processing. What use-case would TrailDB be the obvious, hands-down way to go (vs maybe Postgres + Citus)? [0]: [VIDEO]

    Judson on Hacker News · 2016-05
    In TrailDB – An Efficient Library for Storing and Processing Event Data

  • If you haven't already seen it, Dan from Heap Analytics has a great talk about how they use Postgres and Citus. [VIDEO]

    devbug on Hacker News · 2016-08
    In Building a Scalable Postgres Metrics Backend Using the Citus Extension

  • Keep in mind that Heap collects a huge amount of data and has a huge dataset. I like this[1] talk, it gives you an overview of their architecture. Great post though, thank you for sharing. [1] [VIDEO]

    simiano on Hacker News · 2016-09
    In When to Avoid JSONB in a PostgreSQL Schema

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.