Not to diminish the value of this release, but are there any improvements to consistency and availability of the data store?
My understanding of how it all fits together, please correct if wrong: the default datastore is (strongly!) consistent and partition tolerant but sacrifices availability. The new HRD gives you availability and partition tolerance at the cost, potentially, of consistency. You can get an intermediate state by wrapping writes in taskqueue tasks, which I do for writes that can wait but must not fail on the standard datastore.
Some additional details on the HRD tradeoffs are at http://code.google.com/appengine/docs/python/datastore/hr/. The technical underpinnings are described in http://www.cidrdb.org/cidr2011/Papers/CIDR11_Paper32.pdf (warning: this is not a light read).
[Full disclosure -- I used to work at Google and was involved in some of this work.]
The reduced consistency guarantees in HRD involve indexes, because indexes span entity groups. An example: suppose that you set name=foo in record A1, which is part of entity group A. If you then retrieve record A1, that's an operation on entity group A, so you're guaranteed to see name=foo. But if you perform a global query for all records with name == foo, that's an operation on an index, which is outside the entity group and so is not mediated by the entity group's Paxos log. Therefore, your query might not return A1. The index is "eventually" consistent -- it's guaranteed that, eventually, all indexes will be updated. But AFAIK there's no guaranteed upper bound on "eventually". In practice, it should usually be very quick, but only usually.