cockroach VS vitess

Employ distributed databases like CockroachDB, Cassandra, or managed services like Amazon Aurora Global Databases.

In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB), stream processing (e.g., RisingWave), time series analysis (e.g., Timescale), spatial analysis (e.g., PostGIS), and more. For non-professional users seeking to explore vector databases, they can readily download the open-source PostgreSQL or utilize managed services like Supabase and Neon to establish their own basic AI applications. Other than PostgreSQL, several open-source databases, including OpenSearch, ClickHouse, and Cassandra, have implemented their own vector search functionality. You do not need to adopt a new vector database if you have already used these systems.

Postgres-compatible DSQL solutions: Distributed SQL databases that are either Postgres or Postgres-compatible like Citus, Aurora DSQL, and CockroachDB might be the right approach for handling your scale without forcing you to change much of your code. They each have their strengths and weaknesses and the right one for you depends on your use cases and needs.

Still very much "open-source": https://github.com/cockroachdb/cockroach

But relicensed to the "CockroachDB Software License" as a form of BSL to prevent reselling.

code in a given file is licensed under the BSL and ..." That is sucky.

[0] https://github.com/cockroachdb/cockroach?tab=License-1-ov-fi...

CockroachDB — Distributed SQL database built for cloud applications.

CockroachDB is a distributed SQL database designed for cloud applications. It provides strong consistency, horizontal scalability, and high availability.

1 . Vitess (Sharding layer for MySQL)

Vitess MySQL sharding at hyperscale. Used by YouTube, Slack, and more. Basically MySQL on steroids for distributed environments.

> I am wondering, why it took so long for something like this to happen for Postgres

> We were thinking about adding PostgreSQL support to Vitess several years ago. However, we realized that it would be more efficient if each tool was focused on a specific task.

https://github.com/vitessio/vitess/issues/7084#issuecomment-...

Apart from being backed by Postgres instead of MySQL, is this different from Vitess (and its commercial vendor PlanetScale)?

https://vitess.io/

Never tried myself, but there is Vitess as well that should do what you ask - not sure about the limitations. https://vitess.io/

With Vitess likely merging a lot of its binaries into a single unified binary: https://github.com/vitessio/vitess/issues/7471#issuecomment-...

... it would be a wild future if Vitess replaced the underlying MySQL engine with this as long as the performance is good enough.

Thank you for the compliment!

We recently started adding support for CTEs in Vitess! You can check out https://github.com/vitessio/vitess/pull/14321 if you want to see some technical details of the implementation.

For now, we have added preliminary support by converting them to derived tables internally, but we believe that we need to make CTEs first-class citizens themselves of query planning. Once we make that change, we can look towards supporting recursive CTEs.

This however will take some time, but then, all good things do!

Why would it be a Google project? https://github.com/vitessio/vitess

This is great news. I strolled around https://github.com/vitessio/vitess/issues/12967.

Are there any public discussions of more trade-offs vitess has to make to enable fks?

MySQL + Vitess I noticed Slack gets by using MySQL because they're using Vites. From Slack's post (https://slack.engineering/scaling-datastores-at-slack-with-vitess/) it seems like they choose Vites because it facilitated a smooth transition because it's built on top of MySQL.