How not to use an ORM with SQL Server. January 2. 01. 2The Entity Framework has come a long way since its earliest incarnations prompted a vote of no confidence from the development community. The short answer is yes, there are really good reasons. As a matter of fact there are cases where you just cannot use an ORM. Case in point, I work for a large enterprise financial institution and we have to follow a lot of security guidelines. To meet the rules and. If you follow that blog or know me than the title may shock you a little. Even if you do not know me, you might think I am crazy. Entity Framework (ef) is THE framework used in enterprise and it THE Microsoft’s ORM. It is not that I haven’t try to like it. README.md Benchmarks Benchmarks for ASP.NET Core including (but not limited to) scenarios from the TechEmpower Web Framework Benchmarks. Running the benchmarks The benchmark repo is set up to work against the latest sources (i.e. ASP.NET (originally called ASP+) is the next generation of Microsoft's Active Server Page (ASP), a feature of their Internet Information Server (). Both ASP and ASP.NET allow a Web site builder to dynamically build Web pages on the fly by inserting queries to a. The first preview release of ASP.NET 1.0 came out almost 15 years ago. Since then millions of developers have used it to build and run great web applications, and over the years we have added and evolved many, many capabilities to it. I'm excited today to post about a new release of ASP.NET that we. Despite growing maturity the framework still suffers from problems that often stem from naive implementations. Some of these problems are related to limitations inherent in Object\Relational Mapping (ORM) tools. They only provide partially successful abstractions of relational databases and tend to be complex to implement, mainly because they are trying to solve a very difficult problem. You are trying to synchronise two very different representations of data that are used in two very different contexts. This need not be a barrier to using ORM technologies successfully. The Entity Framework can. However this can be an abstraction too far – it is a mistake to think that you don. What be convenient in a development environment can backfire and become a major bottleneck once it goes live. One of the strengths of ORM tools is that they provide developers with an abstraction that makes it easier to write data access code. However this can be an abstraction too far – it is a mistake to think that you don. Many ORM implementations run into trouble because of a na. Developers should take care with LINQ statements that they write as the Entity Framework won. There does come a point at which another option such as a custom stored procedure or database view should be considered. Most DBAs would prefer data access to be controlled through stored procedures rather than relying on framework- generated SQL. Not only will it tend to perform better but it is easier to secure as the consuming account does not have to be given direct access to data tables. Inappropriate usage scenarios. One of the more common performance complaints about the entity framework is that it is slow for bulk updates. The Entity Framework is primarily designed to make it easier to string up CRUD operations and simple retrieval scenarios. Ideally, you should only fetch the data you really need in order to minimise the amount of unnecessary data querying. In practice it can be difficult to define those objects that should be loaded lazily and those that should be loaded more eagerly. A mixed solution can become a confusing source of bugs and it can be very difficult to define a consistent strategy that meets every usage scenario. Ultimately, you need flexibility over your fetching strategy and a one- size- fits- all approach is likely to be inefficient. Some approaches advocate defining an abstracted fetching strategy that can be passed into data methods but this may risk peppering your data access code with implementation detail. Tight coupling. Loose coupling is often more difficult to achieve than it may first appear. It is time consuming to implement, can create complexity and the benefits are not immediately obvious in a development project. That said, without loose coupling an application can become almost impossible to maintain over the long term. These maintenance difficulties become particularly acute when different tiers of an application are closely bound together. Separate application tiers do not always evolve at the same rate and you are likely to want to be able to change particular implementations without creating a ripple effect throughout the system. The Entity Framework does help in creating an abstraction between the physical database and data access code, but it. A common anti- pattern is to expose Data. Set objects directly to client applications as this ensures a tight bonding between the Entity Framework and the rest of the solution. An application that interacts with your data should not need to know anything about the data access technology. The litmus test is whether your client applications need a reference to the Entity Framework to work. If you isolate your data access technology from your client applications then you are free to evolve their implementation free of any unnecessary dependencies. Clashing contexts. The Entity Framework relies on a Data Context object to provide data access and these management of these objects is a common source of problems. Given that contexts can provide facilities to track changes to entities the temptation can be to keep them open for longer than you need to. This is an anti- pattern as you should aim to use a context for a single operation and drop it as soon as you are finished. Without close control of the database context there is a risk that you will develop serious concurrency problems as your contexts start to conflict with each other. This problem can be countered by using the Unit of Work pattern along with a Repository to regulate access to the database context. The Unit of Work pattern in turn can be used to ensure the proper management of a single, consistent data context. Used together, these patterns help to ensure that you keep track of data operations and manage the way they are written to the database in a consistent way. Stateful services. In a client- server solution, real problems can set in if you try and keep your context alive between different service calls. If you associate a context with a session you can track changes to entities by keeping the context alive between requests. This approach may seem straightforward, but it creates a number of problems. For starters, managing contexts between service calls is a complex undertaking and it can create serious scalability issues as you spin up a new set of resources to service each client. Keeping a client associated with a particular context object is an unnecessary overhead when a completely stateless approach will be easier on resources and give rise to a far less complex solution. If there is any information that needs to be persisted between service calls then you should consider managing this on the client rather than trying to maintain an affinity between sessions and contexts. Filed under Architecture, C#, Design patterns, SQL Server.
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