[ttfkam]

It's not 1992 anymore. https://youtu.be/8Fb5Qgpr03g?si=Jc7dpuVgws3POiXA

It may upset someone's sense of "purity", but the SQL standard and thoughts about the relational model have long since moved on from this dogmatic view of atoms, and no, foreign keys can't perfectly model what folks need. Eventually the rubber hits the road, theory and practice diverge, and different approaches are clearly needed.

There is a place for a document atom in a database (JSON, XML, etc. that don't map well or efficiently to a traditional relational model). For arrays. (Putting in a separate table with its own PK to join is somehow more flexible? Just use unnest(…) for that.) For label trees. For geometries (GIS). For references to tables on other servers (SQL/MED). For tuples. For UUIDs. For ranges. For intervals.

You may call Date and Darwen's work fan fiction, but I have seen tremendous efficiency gains over the last few decades from engines drawing upon their insights without compromising data integrity. In fact, exclusion constraints with timestamp ranges is one area where the old strict relational model would be wholly ineffective for data integrity and avoiding race conditions cascading out to the application level.

https://www.cybertec-postgresql.com/en/postgresql-exclusion-...

[bazoom42]

I belive in using the right tool for the job, and this might somtimes be document databases, key-value stores, xml or json values or whatever is needed to solve the problem.

But let me point out that hierachical databases (which document databases, xml etc are variants of) predate the relational model (and certainly predate Dates work) so it it worth to be aware of the challenges and limitations which caused the development of the relational model as an alternative.

[ttfkam]

> I belive in using the right tool for the job

And more of these tools (RDBMSs) are able to perform more jobs. There's definitely use cases for correlating parts of documents with traditional relational data. Quite often there's no need to choose between a relational database engine and a document database engine when the engines support both and more.

Hybrids tend to blur the lines for definitions.