I wonder if it's possible to create a logic that automatically creates a denormalized table and it's data (and maintains it) by a specific SQL-like query.
Given a system where the user can maintain his data model and data. All data are stored in "relational" tables, but those tables are only used for the user to maintain his data. If he wants to display data on a webpage he has to write a query (SQL) which will automatically turn into a denormalized table and also be kept up-to-date when updating/deleting the relational data.
Let's say I got a query like this:
select t1.a, t1.b from t1 where t1.c = 1
The logic will automatically create a denormalized table with a copy of the needed data according to the query. It's mostly like a view (I wonder if views will be more performant than my approach). Whenever this query (give it a name) is needed by some business logic it will be replaced by a simple query on that new table.
Any update in t1 will search for all queries where t1 is involved and update the denormalized data automatically, but for performance win it will only update the rows infected (in this example just one row). That's the point where I'm not sure if it's achievable in an automatic way. The example query is simple, but what if there are queries with joins, aggregation or even sub queries?
Does an approach like this exist in the NoSQL world and maybe can somebody share his experience with it?
I would also like to know whether creating one table per query does conflict with any best practises when using NoSQL databases.
I have an idea how to solve simple queries just by finding the involved entity by its primary key when updating data and run the query on that specific entity again (so that joins will be updated, too). But with aggregation and sub queries I don't really know how to determine which denormalized table's entity is involved.