I would love to know this information as well, but I was unable to find any further discussion by The Guardian or others in a similar situation.
My understanding is that given the technical challenges in switching to SQL from NoSQL, even with the JSONB column type, that it took the entire engineering team an entire year to make the switch.
So I cannot imagine the cost of the entire software development team for an entire year compares in the least to any other costs.
From that point of view, I do not think they would ever consider another switch, because using an entire engineering team for a year is pricey.
The Guardian developers did not mention whether they purchased a support contract for PostGreSQL. If they did, they would have had to do so through a third-party offering professional support to Europe, because Postgres is free software that does not offer its own commercial support contracts.
Maybe they will get back to me
You inspired me to ask the development team on Twitter about exactly what we both want to know, so hopefully I will hear something back:
The JSONB format
On your point about the JSONB format not being a “document” store, I think I understand you to mean that any “document database” like NoSQL does not only store “documents” — it stores key-value pairs.
Obviously these key-value pairs could store arbitrary data and meta-data, not just documents, but typically NoSQL is a great fit for text-heavy content.
Meanwhile, SQL is going to be a better fit for tabular data, especially data that contains a lot of numbers — though either could be used for either case.
R. S. Harding — Please correct me if I am misunderstanding things!
Here is what AWS has to say about document databases:
The document database defined
A document database is a type of nonrelational database that is designed to store and query data as JSON-like documents. Document databases make it easier for developers to store and query data in a database by using the same document-model format they use in their application code. The flexible, semistructured, and hierarchical nature of documents and document databases allows them to evolve with applications’ needs. The document model works well with use cases such as catalogs, user profiles, and content management systems where each document is unique and evolves over time. Document databases enable flexible indexing, powerful ad hoc queries, and analytics over collections of documents.