PostgreSQL is enough (2024)

PostgreSQL is enough (2024)

@cpursley

@LrWm3

@kenfar

@cpursley – no product is needed, just the right features:

  • partitioning
  • query parallelism
  • dimensional model (rather than say one-big-table)
  • pre-computed aggregate tables for common queries
  • appropriate hardware (sufficient memory, cpu, maybe very fast IO)

This is missing an MPP configuration (data distributed across multiple servers working together on queries), and columnar structures. But, those aren’t absolutely essential.

@mjf

@cpursley

@brianheineman

I’ve recently put together the Rust crate postgresql-embedded that will allow you to embed PostgreSQL into an executable for use in environments where downloading the installation may not be an option.

@WesleyYue

@mahrous-amer

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@docwhat

@philippemnoel

@AdnanSoftic

@Mdkar

Not sure if it’s any good, but PostgresML claims to do RAG infra (for use with LLMs and chat bots).

@secp256k1-sha256

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Amazing list, very helpful.

Scaling section can be improved further.

Connection Pools and Load balancers: (similar to Supavisor added by you)
PgCat
PgBouncer
PgPool-II

Sharding:
Citus can be under scaling as well due to sharding capability.

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I am not sure below Postgres derivatives can be part of the list as they are not open source but they are part of Postgres compatible scaling solutions.
Distributed Postgres flavors:
Yugabyte
Multi-master Postgres derivatives for scaling :
Spock
EDB Postgres-distributed
AWS PGACTIVE

@CC-Hsu

I’d like to know how postgres can join to the blockchain world since this is a less discussed topic.

@cassandrastumer

@abeisleem

@gregdingle

Edgedb should be in there somewhere.

@bkovacev

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I would love to see some self hosting best practices and gotchas!

@xenophenes

@ityler

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@rodafr

@divyam234

@varun-dhawan

Great repo – @cpursley !!

I’d suggest adding this 5-part blog series on advanced data science with PostgreSQL window functions:
https://data-nerd.blog/tag/window-functions/

Covers ranking, rolling stats, gaps/islands, and more—pure SQL, no external tooling. Could fit under Analytics or Advanced SQL with PostgreSQL.

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@maelp

@maelp

@alice-viola

I’m the author of QueenMQ, a C++ queue system backed by Postgres; we replaced Kafka with it in some of our B2B SaaS products.

Is also available as pg extension, that reproduce Kafka semantics directly from SQL. So you can use it without the server and the client, if needed.

@cpursley

@beh74

@levkk

@umrashrf

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