Comment by refset | Hacker News Reader

Comment by refset | Hacker News Reader

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I'm not convinced about that comparison. MongoDB entirely disregarded the relational model whereas bitemporality—as envisioned by Snodgrass et al. and standardised in SQL:2011—is merely an extension/evolution of it.

> it would be cool if e.g. Postgres had fast native support for bitemporal fields in a way that makes them accessible without changing the whole paradigm

100% agreed with you there. And there has been various work on patches & extensions in this area previously. Unfortunately I'm not sure Postgres' internals will ever be able to flex hard enough to deliver a decent "default choice" experience. At least not until some other system has proven the UX is really worth the effort (which I guess MongoDB did similarly achieve with native JSON handling).

As it turns out, other mature options offer this temporality out of the box. In Fauna (disclaimer: I work there) offers temporality out of the box so you can do a search on a record at a specific point in time in the past. It combines this with native JSON documents with flexible schema (so you can add additional notes as an audit trail) without disregarding relational modeling (it supports joins, foreign keys, normalization, etc.), and with low-latency distributed ACID writes nd transactions. A couple of other databases were mentioned here (Datomic and xtdb) that support this, and I believe it is just a matter of time where this will be more widely used. Two additional points to make: a) to the comment of "let's avoid RDBMS schema/migration hell by making everything a flexible JSON document" - that's a specific side effect of Mongo's design decision - since our db handles schema migrations quite elegantly, so I wouldn't be quick to assume that because Mongo did it that way that most systems will exhibit those side effects. b) The main reason I'm convinced this will be used a lot more (call it event-driven systems, temporal systems, etc) is because it will result in better-trained ML behavioral and prediction models too. So, might as well get ahead of this.

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