(Ozgun from Citus Data) What really excites me about this blog post is how PostgreSQL is becoming central across diverse workloads - including real-time analyt

(Ozgun from Citus Data) What really excites me about this blog post is how PostgreSQL is becoming central across diverse workloads - including real-time analytics. A few Postgres resources that relate to this blog post are the following. 1. TopN: Several Citus customers were already using the TopN extension. Algolia contributed to revising the public APIs in this extension. With these revised APIs, we felt pretty comfortable in open sourcing the extension for the Postgres community to use: https://github.com/citusdata/postgresql-topn https://github.com/citusdata/postgresql-topn 2. Postgres JIT improvements: Postgres 11 is coming with LLVM JIT improvements. For analytical queries that run in-memory, these changes will improve query performance by up to 3x. This will significantly speed up roll-up performance mentioned in this blog post: https://news.ycombinator.com/item?id=16782052 https://news.ycombinator.com/item?id=16782052 3. For those interested, this tutorial talks about how to build real-time analytics ingest pipelines with Postgres: https://www.youtube.com/watch?v=daeUsVox8hs https://www.youtube.com/watch?v=daeUsVox8hs