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I’ve been doing some reasonably serious playing with the idea of using jsonb columns as a kind of front end to relational tables. So basically, external interac

I’ve been doing some reasonably serious playing with the idea of using jsonb columns as a kind of front end to relational tables. So basically, external interactions with the database are done using JSON, which gives end users some flexibility, but internally we effectively create a realtime materialised view of just those properties we need from the json. Anyone else tried this approach? Anything I should know about it?

hdhshdhshdjd 2y ago
I do something similar, building a lightweight search index over very large relational datasets. So the tables are much simpler to manage, much more portable, so I can serve search off scalable hardware without disturbing the underlying source of truth. The downside is queries are more complex and slower.
Zenzero 2y ago
My mental model has always been to only use JSONB for column types where the relations within the json object are of no importance to the DB. An example might be text editor markup. I imagine if you start wanting to query within the json object you should consider a more relational model.
- doctor_eval 2y ago
  My experience has been that users like to include a lot of information that's not relevant to the application I'm working on. My application couldn't really care less about customer names, for example. But the people who buy my software naturally do care - and what's worse, each of my potential customers has some legacy system which stores their customer names in a different way. So one problem I want to address is, how do I maintain fidelity with the old system, for example during the data migration, while enabling me to move forward quickly? My solution has been to keep non-functional data such as customer names in JSON, and extract only the two or three fields that are relevant to my application, and put them into a regular SQL database table. So far this has given me the best of both worlds: a simple and highly customisable JSON API for these user-facing objects with mutable shapes, but a compact SQL backend for the actual work.
- mbesto 2y ago
  I always thought JSONB is a great use case for client-specific customizations. For example - a CRM application where you have structured DB tables like "account", "opportunity", etc. but then a client-specific table might be "cohort" that is linked to "account" and has fields "cohort size", "cohort name", etc. You just chuck the cohort table in JSONB and now the company who uses the CRM that has the custom cohort table can change that table without creating/migrating your RDMS table structure. Curious what other people think here?
  - Zenzero 2y ago
    That sounds like something that would be better tailored to well normalized tables and custom row entries. The question I'd ask is if something you're concerned about being a column could instead be a row in a different table.

hdhshdhshdjd 2y ago

I do something similar, building a lightweight search index over very large relational datasets. So the tables are much simpler to manage, much more portable, so I can serve search off scalable hardware without disturbing the underlying source of truth. The downside is queries are more complex and slower.

Zenzero 2y ago

My mental model has always been to only use JSONB for column types where the relations within the json object are of no importance to the DB. An example might be text editor markup. I imagine if you start wanting to query within the json object you should consider a more relational model.

doctor_eval 2y ago
My experience has been that users like to include a lot of information that's not relevant to the application I'm working on. My application couldn't really care less about customer names, for example. But the people who buy my software naturally do care - and what's worse, each of my potential customers has some legacy system which stores their customer names in a different way. So one problem I want to address is, how do I maintain fidelity with the old system, for example during the data migration, while enabling me to move forward quickly? My solution has been to keep non-functional data such as customer names in JSON, and extract only the two or three fields that are relevant to my application, and put them into a regular SQL database table. So far this has given me the best of both worlds: a simple and highly customisable JSON API for these user-facing objects with mutable shapes, but a compact SQL backend for the actual work.
mbesto 2y ago
I always thought JSONB is a great use case for client-specific customizations. For example - a CRM application where you have structured DB tables like "account", "opportunity", etc. but then a client-specific table might be "cohort" that is linked to "account" and has fields "cohort size", "cohort name", etc. You just chuck the cohort table in JSONB and now the company who uses the CRM that has the custom cohort table can change that table without creating/migrating your RDMS table structure. Curious what other people think here?
- Zenzero 2y ago
  That sounds like something that would be better tailored to well normalized tables and custom row entries. The question I'd ask is if something you're concerned about being a column could instead be a row in a different table.