@jherazob what are you thoughts on this approach?:Supabase Vault

I'm only vaguely aware of the existence of Supabase and have never really evaluated it before, so will have to give it a good look before forming an opinion, gut feeling still tells me that secrets on the DB is probably not good but i have to analyze their approach to give it a fair assessment

@cpursley something that can be added to Audit Logs:https://github.com/BemiHQ/bemi

Great! That this idea is getting traction :-)

This is missing data warehousing, reporting and analytics.

@kenfar Any suggestions for those?

@cpursley@kenfar its deprecated but technically tobs can be salveged for this purpose:https://github.com/timescale/tobs

@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.

MyPostgres collection, perhaps you'd like to use some of the items as well. Here is my list ofPostgres blogs worth visiting regularly.

These are great@mjf, thanks! I added a link undermiscellaneous.

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

@cpursley@kenfar checkouthttps://github.com/hydradatabase/hydra andhttps://github.com/paradedb/paradedb for analytics/column stores.

I have been usinghttps://github.com/sqitchers/sqitch for a while on production to handle migrations with Postgres it works perfectly.

https://graphjin.com for purely GraphQL API goodness?

For analytics:

pg_lakehouse (by ParadeDB):https://github.com/paradedb/paradedb/tree/dev/pg_lakehouse -- Fast analytics from Postgres over local Parquet files, data lakes (S3, GCS, etc.), and lakehouses (Delta Lake, Iceberg)

pg_analytics (by ParadeDB):https://github.com/paradedb/paradedb/tree/dev/pg_analytics -- Columnar storage in Postgres for fast analytics inside Postgres tables

For NoSQL:

https://martendb.io/

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

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 tosharding capability.

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

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

For scaling:https://github.com/postgresml/pgcat

For search:https://github.com/postgresml

For RAG/ML/AI:https://github.com/postgresml

recommend addinghttps://anyblockers.com/posts/postgres-as-a-search-engine under #Search

Edgedb should be in there somewhere.

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

https://codeberg.org/Data-Bene/StatsMgr was just introduced as advanced statistics management

GIS/Mapping:https://github.com/pgRouting

Cloud native Postgres:https://cloudnative-pg.io/

Worth mentioning pgroonga for advanced multilingual searchhttps://pgroonga.github.io/

Great repo -@cpursley !!

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

Coversranking,rolling stats,gaps/islands, and more—pure SQL, no external tooling. Could fit underAnalytics or Advanced SQL with PostgreSQL.

This is interesting toohttps://www.malloydata.dev/ andhttps://github.com/malloydata/malloy

Also DBOS and Absurd
https://github.com/dbos-inc/
https://github.com/earendil-works/absurd

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