- JSON / jsonb
- improved partitioning support
- identity columns
I agree that I wouldn't want to trust a new entrant to the space unless it was subject to rigorous testing, eg https://jepsen.io/
Postgres has the advantage that it's still open-source, can be ran locally and self-hosted (and has a healthy ecosystem of managed providers) and won't go away anytime soon. None of these are true for all these new DB startups.
- The product has bugs not addressed by Jepsen.
- Performance is inadequate.
- The optimizer is immature, and you find yourself struggling to understand and work around its limitations.
- Replication is missing or doesn't work well enough.
- There is absolutely no substitute for N years of real-world experience, no matter how rigorous the company's testing.
- Impossibility of finding people already familiar with the product, because they are all employed by the vendor.
- Even aside from product issues, is the company profitable? If not, how long is it going to be in existence?
I've actually seen the results of a database product being picked, the company behind which ceased to exist. It wasn't pretty, since at one point the product ceased to be supported and therefore neither any updates/fixes were made, it wasn't available in the repositories for new OS distros and eventually even the documentation for it went offline. Having to support a system that integrated with it was an unpleasant experience, all the way to it being eventually replaced with something else instead.
Therefore, it probably makes a lot of sense to base something as critical as your data storage layer on proven technologies that have demonstrated that they'll probably be supported in one form or another for the following years or even decades, unless you have a good reason for choosing something else.
Those reasons might deal with particular workloads or requirements, e.g. clustering solutions for PostgreSQL/MySQL/MariaDB/..., geospatial extensions, solutions to integrate with it through REST interfaces or even GraphQL or something like that, with a stable and proven piece of software still at the core of it all.
In case anyone is wondering, the product in question was Clusterpoint, about which you can read a bit more here: https://en.wikipedia.org/wiki/Clusterpoint a NoSQL database that actually predates MongoDB by a few years, as far as i know. Of course, now it seems like even their homepage is offline.
> Clusterpoint Ltd.
> Founded 2006
> Clusterpoint Database
> Initial release 2006
> Stable release 2015
MongoDB: https://en.wikipedia.org/wiki/MongoDB
> MongoDB, Inc. (formerly 10gen, Inc.)
> Founded 2007
> MongoDB
> Initial release 2009
> Stable release 2021
Then again, maybe Clusterpoint's Wikipedia page is lying, i don't really care much about it anymore.