Abstract Data Use Not Data Access

Common data access abstractions I've come across and been guilty of implementing myself are the likes of:

The problem is, these are not really abstractions. If anything they add an extra layer of indirection. One such benefit of this level of indirection is each concrete implementation can be substituted. This makes testing easy. Other than this, such generic solutions introduce a whole host of problems.



Such examples are said to be at the wrong level of abstraction. This indirection forces developers to work at the wrong level of abstraction. For example, a controller has no right to be directly querying your data store directly. If the same query is required somewhere else you introduce duplication.

Big Bang Upgrade

Given such indirection offers a poor abstraction, upgrading to use a different implementation is tricky. If we assume one hundred usages of IDatabase, all of these code paths need to be migrated and tested. This can be such a huge undertaking that upgrades are often left as technical debt, never to be fulfilled.

Leaky Abstractions

In a similar manner to the previous point, these abstractions are poor. They leak implementation details. Due to this they cannot be considered as valid abstractions. Consider a SQL implementation of IDatabase, we may have a FindById method that takes an integer as the Id. If we wished to update to a NoSQL solution the lack of a primary key causes problems. FindById for the NoSQL implementation may require a Guid. There interface is now broken.

Interface Bloat

Another downside of coding at the wrong level of abstraction is that the amount of use cases increase constantly. What might begin as a humble interface consisting of a handful of query methods soon becomes a dumping ground for all sorts of exotic behaviour - specific to niche use cases.

Lowest Common Denominator

Different data access providers have different capabilities, but in order to stay "decoupled" only core functionality present in all providers can be used. This leads to dull, limited interfaces consisting of standard data access functionality. The limited feature set can mean a poor integration. Why avoid the advanced features your library offers?

A poor abstraction that exhibits the problems above may look like this.

To retrieve a user based on the Id.


If we abstract how the data is used and not how the data access is performed we can avoid these pitfalls. By staying at the right level of abstraction and not leaking implementation details we end up with a different looking interface.

The concrete implementation in this example will be a SQL implementation using Dapper.NET.

The usage is similar.

The key point here is that we solve the problems of the "generic" solution.

Aren't We Introducing Lots of Classes?

More, but not "lots". However this is a common complaint when the above solution is proposed, though given the vast benefits included this trade off is certainly worth it. Additionally, each query or repository that is implemented in this manner is easier to develop and test due to closer adherence to the Single Responsibility Principle.

How Do We Unit Test SqlUserQuery?

You don't. In this example we make use of the third party library directly. The benefits discussed prior justify this, though it means unit testing is not possible. Therefore you should apply integration testing against a real data store. The rest of the system will be coded against the abstraction, so unit tests can be applied as normal here. Any attempt to "abstract" or wrap the third party will remove many of the benefits of this solution, so don't worry about it.

For a great discussion on this topic, check out a talk by Kijana Woodard for more examples.