Skip to main content

Entity Framework - Hybrid Code First

Let's talk about an interesting subject related to Entity Framework (EF). When you are using EF there are different mechanism to map your model:
  • Code First - we write the code first and the DB is generated automatically based on the code
  • Database First - we define the DB structure and POCO entities are created automatically
  • Model First - we design the model in a 'nice' designer. This designer will generate the classes and the database model
All of them are perfect and works great. Based on our needs, preferences and team skills we can decide to go with an approach or another, but in the end we will end up with the same thing. I will follow up later on with a different post where I will compare them.

Now, let's talk about different scenarios that is used by people. I saw in a lot of implementation where people are afraid of Code First or Model First. Because of this I realize that most of them are using a hybrid solution that I called Hybrid Code First.

Why I called Hybrid Code First? 
Well, people don't trust EF to generate the database schema. Because of this they are defining the model in the code as classes (POCO). Once this is done, they are defining the database schema - tables, indexes, keys, the relationship between entities. 
Once this step is done, they are defining the mapping between their classes (POCO) and database schema using Fluent API. In this way they are connecting each C# entity model to each table, column or key.

Is this a good approach?
Well...there is no the right answer. This approach it is used because people don't trust EF enough. People don't trust that EF can generate a database schema good enough. Based on this fears they combine Code First with Database First using Fluent API. 
This way they have full control to database schema and also to the model (C# entities). 
Of course, because of this versioning needs to be made manually, but they don't trust out of the box versioning of Code First, even if with EF 4.1 version, it works pretty great.

This is another approach to define and manage the entities model. Even if it is more time consuming, it offers a safety nest for developing team. Offering them control for both part (DB and Code).  

Comments

  1. We are using exactly this model - and not because we don't trust EF to generate the database create/update scripts - it's because very often the DB schema can't be inferred only from the mappings.

    An example:
    - all C# classes are mapped to database views, that perform (custom) queries over the DB tables - how could EF by itself generate such a database? :)

    ReplyDelete

Post a Comment

Popular posts from this blog

Why Database Modernization Matters for AI

  When companies transition to the cloud, they typically begin with applications and virtual machines, which is often the easier part of the process. The actual complexity arises later when databases are moved. To save time and effort, cloud adoption is more of a cloud migration in an IaaS manner, fulfilling current, but not future needs. Even organisations that are already in the cloud find that their databases, although “migrated,” are not genuinely modernised. This disparity becomes particularly evident when they begin to explore AI technologies. Understanding Modernisation Beyond Migration Database modernisation is distinct from merely relocating an outdated database to Azure. It's about making your data layer ready for future needs, like automation, real-time analytics, and AI capabilities. AI needs high throughput, which can be achieved using native DB cloud capabilities. When your database runs in a traditional setup (even hosted in the cloud), in that case, you will enc...

How to audit an Azure Cosmos DB

In this post, we will talk about how we can audit an Azure Cosmos DB database. Before jumping into the problem let us define the business requirement: As an Administrator I want to be able to audit all changes that were done to specific collection inside my Azure Cosmos DB. The requirement is simple, but can be a little tricky to implement fully. First of all when you are using Azure Cosmos DB or any other storage solution there are 99% odds that you’ll have more than one system that writes data to it. This means that you have or not have control on the systems that are doing any create/update/delete operations. Solution 1: Diagnostic Logs Cosmos DB allows us activate diagnostics logs and stream the output a storage account for achieving to other systems like Event Hub or Log Analytics. This would allow us to have information related to who, when, what, response code and how the access operation to our Cosmos DB was done. Beside this there is a field that specifies what was th...

[Post Event] Azure AI Connect, March 2025

On March 13th, I had the opportunity to speak at Azure AI Connect about modern AI architectures.  My session focused on the importance of modernizing cloud systems to efficiently handle the increasing payload generated by AI.