Suggestions
Craig Kerstiens
Product at Crunchy Data
Craig Kerstiens is the Chief Product Officer at Crunchy Data, a company specializing in open-source PostgreSQL database solutions. He has extensive experience in product management and engineering, particularly in the realm of data and cloud technologies. Prior to his role at Crunchy Data, Kerstiens held various positions at companies like Heroku, where he focused on product development and strategy.
Kerstiens is known for his expertise in building products that enhance user experience and drive business growth. His background includes significant contributions to the PostgreSQL community, where he has been involved in various initiatives to promote the use of open-source databases. He is also active on LinkedIn, where he shares insights related to product management and technology trends.
Highlights
For as much as it's nothing like actual Postgres, AWS Aurora DSQL does seem like some good and challenging engineering.
My take is very little of existing apps will be migrating to it, at least for 2-3 years until it closes some feature gap. So what need does it address?
It seems like a slightly expanded Dynamo or perhaps closer to GCP's spanner. It speaks SQL, supports standard inserts/updates (as long as on a small to medium set of data - under 10k rows), and joining across data.
Doesn't seem like a tool for most application developers.
This will likely be only for green field apps–purpose built for using it. Very specific use cases that have the shape of problem it solves.
"Just use Postgres" isn't solely about technology, it's about organizational simplicity. For every later you add to your data stack you're adding essentially adding a team.
Just Postgres really does work, and you could see team sizes 1/10 to 1/100 of other organizations.
The real benefit isn't even in the cost savings of having way less people within your org, it's efficiency of working with and acting upon data. Each hop within an organization adds to the time from insight to action.
Think about it as business decision latency.
For every 1 hr of data latency the organizational latency is an orders of magnitude higher.
