Having only read the abstract:
Am I correct assuming this could be used as the core
piece of implementing something like Datomic?
I have been thinking a bit about how amazingly useful
a generic, distributed B-Tree would be, thanks to it's
applicability with immutable data structures.
I think the MVCC features in Minuet are applicable in instances where immutability can be used as an optimization, such as Datomic. However, Datomic has a very specific data model and set of use cases which means they likely optimize in a variety of domain specific ways. More likely I would suspect Minuet is positioned to be the basis for a RDBMS storage engine, or on its own as a powerful key/value store.
Datomic has a very simple concurrency model that makes a sophisticated distributed B-tree like this unnecessary. Minuet carefully manages concurrent access to the data, through snapshots and keeping track of read/write data access per transaction to manage concurrency according to the desired isolated level. Datomic has scalable read-only views, but a serial write transaction executor, so the distribution aspect is fairly simple.
On Minuet, while I do like the area of work, I think it is a mistake to keep track of read and write sets for concurrency control. The performance is not great when you want to do real-time analytical queries. Check Figure 17, where you can see that the throughput barely increases when adding machines for frequent snapshots.
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[ 5.4 ms ] story [ 16.1 ms ] threadI have been thinking a bit about how amazingly useful a generic, distributed B-Tree would be, thanks to it's applicability with immutable data structures.
How I wish they did.
> which means they _could_ optimize in a variety of domain specific ways.
On Minuet, while I do like the area of work, I think it is a mistake to keep track of read and write sets for concurrency control. The performance is not great when you want to do real-time analytical queries. Check Figure 17, where you can see that the throughput barely increases when adding machines for frequent snapshots.