I have not written about it publicly at any length. Much narrower versions targeting specific data models have been used in production and I've licensed bits and pieces to big tech companies. The data structures and algorithms are non-obvious, and the join mechanics that enable arbitrary relationship type traversals on the representation hurts the brain (it really isn't visualizable). It is just an elegant instantiation of adaptive information theoretic embeddings in very high dimensionality spaces, reduced to fast database algorithms. My previous startup was based on related but very early and incomplete computer science, which was written about.

The storage engine is extremely fast but the only unusual capabilities it has are architectural: the ability to continuously, in the background, reshard data (many tens of thousands of times per second per inexpensive server) and shift shards between storage engines. If you think about it, all this really requires from a storage engine is the ability to concurrently create and destroy logical files at an extremely high rate, much higher than a typical file/operating system allows. Some of the internal algorithms are novel but it is still just a storage engine. It is tuned for petabyte storage densities per server -- it was originally designed for exabyte-scale sensor data models.

None of my database work has ever been open sourced AFAIK, though many companies have older designs. The biggest practical hurdle to open sourcing is that it would require many man-months of tedious unpaid work and I have zero desire to do that. It is also a production-grade research project; I currently have no obligation, explicit or implied, to maintain any kind of compatibility if I feel like redesigning some aspect of it. That said, I also want to get away from the current reality that every company wants someone to build their own slight variation of these designs.