Given these primitives, you or other engineers can write higher level APIs on top (e.g. sql, search, etc). In fact, we make extensive use of their RecordLayer [1] library which provides a strongly consistent schema based write process using Protobuf. This includes on-write-consistent indexes. Apple has also open-sourced a MongoDB API [2] compliant interface that allows you to get all the consistency guarantees from FDB, but with an API interaction of MongoDB.
The beauty of FDB is that the primitives are done in such a rock solid fashion, you can write higher level APIs without having to worry about the really hard stuff (transactions, failures, config errors, testing, simulation, etc). Another example is that CouchDB is switching their back-end to use FDB for their 4.0 release.
Given that the database sorts data lexicographical...to us, it became a natural fit for an online (always-mutable) time-series database.
If you want more insight in how we use it, I go over it in some detail towards the end of my keynote [3] from last August.
[1] https://www.foundationdb.org/blog/announcing-record-layer/
We run several FDB clusters using 3-DC replication and have never once lost data. I remember when we wanted to replace all of the FDB hardware (one cluster) in AWS, and so we just doubled the cluster size, waited for data shuffling to calm down, and just started axing the original hardware. We did this all while performing over 100K production TPS.
One thing that makes the above seamless for all existing connections is that clients automatically update their "cluster file" in the event that new coordinators join or are reassigned. That alone is amazing...as you don't have to track down every single client and change / re-roll with new connection parameters.
Anyway, I talk this database up every chance I get. Keep up the awesome work.
- A very happy user.