Peter is the former President of the New Zealand Open Source Society. He is currently working on Business Workflow Automation, and is the core maintainer for Gravity Workflow a GPL workflow engine.
My applications are more like spreadsheets in that the user defines the data structures and relationships. They do this at runtime and the data structures are stored as data, but used when data is submitted. We have introduced referential links between entities and it is possible to create views which traverse the references. We have implemented GraphQL to be able to get data, which is also able to traverse between documents using references.
In relation to maintaining referential integrity because there is no coupling to the domain there really is only one area of the code that needs to worry about this. We reap other benefits from this approach, including a elegant security model which means we have fine grained access controls over what fields and documents are visible to users based on an access control policy.
Trying to author your own aggregations is folly. In our application we have been able to do complex data transformations easily by having easy to configure transforms which generate the aggregations. Doing it by hand would be a living nightmare.
Is MongoDB the best solution for everything? Nah. For highly structured data like telco call records SQL is the way. For apps that are tightly coupled to the domain, which is typically how things have been done, is fine. But... and this is a big but... the way we tightly couple applications to the data model is making our applications less flexible than they need to be.
Schemaless systems are opening the door. Ten years ago I was where you are now; SQL was the light and the truth. Today my view is broader and I have been given good reason to question the accepted orthodoxy. That said we can't be blind to the downsides.
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My applications are more like spreadsheets in that the user defines the data structures and relationships. They do this at runtime and the data structures are stored as data, but used when data is submitted. We have introduced referential links between entities and it is possible to create views which traverse the references. We have implemented GraphQL to be able to get data, which is also able to traverse between documents using references.
In relation to maintaining referential integrity because there is no coupling to the domain there really is only one area of the code that needs to worry about this. We reap other benefits from this approach, including a elegant security model which means we have fine grained access controls over what fields and documents are visible to users based on an access control policy.
Trying to author your own aggregations is folly. In our application we have been able to do complex data transformations easily by having easy to configure transforms which generate the aggregations. Doing it by hand would be a living nightmare.
Is MongoDB the best solution for everything? Nah. For highly structured data like telco call records SQL is the way. For apps that are tightly coupled to the domain, which is typically how things have been done, is fine. But... and this is a big but... the way we tightly couple applications to the data model is making our applications less flexible than they need to be.
Schemaless systems are opening the door. Ten years ago I was where you are now; SQL was the light and the truth. Today my view is broader and I have been given good reason to question the accepted orthodoxy. That said we can't be blind to the downsides.