This is just another way of saying you need to implement your own system for managing consistency. Dynamo offers transactions now, but they don’t offer actual serialization. Your transaction will simply fail if it runs into any contention. You might think that’s ok, just retry. But because you’ve chosen to sacrifice modelling your data, this will happen a lot. If you want to use aggregates in your Dynamo, you have to update an aggregate field every time you update your data, which means you create single points of contention for your failure prone transactions to run into all over your app. There are ways around this, but they all come at the cost of further sacrificing consistency guarantees. The main issue with that being that once you’ve achieved an inconsistent state, it’s incredibly difficult to even know it’s happened, let alone to fix it.
Then you run into the issue of actually implementing your data access. With a denormalized data set, implementing all your data access comes at the expense of increasing interface complexity. Your schema ends up having objects, which contain arrays of objects, which contain arrays... and you have to design all of your interfaces around keys that belong to the top level parent object.
The relational model wasn’t designed to optimize one type of performance over another. It was designed to optimize operating on a relational dataset, regardless of the implementation details of the underlying management system. Trying to cram a relational set into a NoSQL DB unavoidably comes at the expense of some very serious compromises, with the primary benefit being that the DB itself is easier to administer. It’s not as simple as cost of storage vs cost of compute. NoSQL DBs like dynamo (actually especially dynamo) are great technology, with many perfectly valid use cases. But RDBMS is not one of them, and everybody I’ve seen attempt to use it as an RDBMS eventually regrets it.
No comments yet.
