HyperDex provides scalable and high-performance transactions. While it is strongly (not eventually) consistent, the underlying technique we use to achieve atomicity of transactions is reminiscent of this approach.
On a related note, our experience is that a tightly implemented database can be much faster than a typical eventually consistent database. It would be great to see performance comparisons from TreodeDB.
That's cool. Indeed, it does look like one could use HypderDex's transactions and cond_put to make something close the batch write described in this post.
However, I don't see the part about Lamport clocks in HyperDex's API. Maybe one could implement that in a layer on top. The technique in the post allows a client to know if the values in its cache satisfy application invariants, even invariants that relate multiple rows. The Lamport clocks are key to making that part work.
I would very much like to provide performance numbers, and Jepsen results, and more for TreodeDB. Along that line though, I'm looking for contributors (or even a co-founder). I've gotten it this far on my own, but I really need help.
