Agreed, this is accurate. I work on XTDB and was able to speak with Richard Snodgrass (author of the paper) a couple of years ago. During our conversation we discussed how his research was primarily focused on handling valid-time, with transaction-time (a.k.a. system-time per SQL:2011) as a secondary concern. In contrast XTDB was inspired by the functional programming / immutability / database-as-a-value vision behind Datomic but with a desire for something more powerful than just the transaction-time capabilities. Essentially we arrived at 'bitemporal' from the opposite direction. This blog post covers the perspective somewhat: https://vvvvalvalval.github.io/posts/2017-07-08-Datomic-this...
I believe people interested in the latter are almost always interested in the former also, at least in the context of transactional systems (and particularly anything subject to complex regulatory requirements).
Analytical systems are a different world where time seems to often be regarded as "just another dimension", but strong consistency and auditability are increasingly relevant there too, which is also a natural reflection of how a lot of modern OLAP systems operate internally using immutable snapshots of blob storage (see Snowflake, Iceberg, LakeFS etc.).
As it turns out, AsOf in SQL is a problem I ran into just yesterday when ensuring that serialized report snapshots point to the correct historical versions of their resources.
