What should I use for performance sensitive data access?

So I have an application which requires very fast access to large volumes of data and we're at the stage where we're undergoing a large re-design of the database, which gives a good opertunity to re-write the data access layer if nessersary!

Currently in our data access layer we use manually created entities along with plain SQL to fill them. This is pretty fast, but this technology is really getting old, and I'm concerned we're missing out on a newer framework or data access method which could be better in terms of neatness and maintainability.

We've seen the Entity Framework, but after some research it just seems that the benefit of the ORM it gives is not enough to justify the lower performance and as some of our queries are getting complex I'm sure performance with the EF would become more of an issue.

So it is a case of sticking with our current methods of data access, or is there something a bit neater than manually creating and maintaining entities?

I guess the thing that's bugging me is just opening our data layer solution and seeing lots of entities, all of which need to be maintained exactly in line with the database, which sometimes can be a lot of work, but then maybe this is the price we pay for performance?

Any ideas, comments and suggestions are very appreciated! :)

Thanks,

Andy.

** Update **

Forgot to mention that we really need to be able to handle using Azure 开发者_如何学C(client requirements), which currently stops us from using stored procedures. ** Update 2 ** Actually we have an interface layer for our DAL which means we can created an Azure implementation which just override data access methods from the Local implementation which aren't suitable for Azure, so I guess we could just use stored procedures for performance sensitive local databases with EF for the cloud.

I would use an ORM layer (Entity Framework, NHibernate etc) for management of individual entities. For example, I would use the ORM / entities layers to allow users to make edits to entities. This is because thinking of your data as entities is conceptually simpler and the ORMs make it pretty easy to code this stuff without ever having to program any SQL.

For the bulk reporting side of things, I would definitely not use an ORM layer. I would probably create a separate class library specifically for standard reports, which creates SQL statements itself or calls sprocs. ORMs are not really for bulk reporting and you'll never get the same flexibility of querying through the ORM as through hand-coded SQL.

Stored procedures for performance. ORMs for ease of development

Do you feel up to troubleshooting some opaque generated SQL when it runs badly...? That generates several round trips where one would do? Or insists on using wrong datatypes?

You could try using mybatis (previously known as ibatis). It allows you to map sql statements to domain objects. This way you keep full control over SQL being executed and get cleanly defined domain model at the same time.

Don't rule out plain old ADO.NET. It may not be as hip as EF4, but it just works.

With ADO.NET you know what your SQL queries are going to look like because you get 100% control over them. ADO.NET forces developers to think about SQL instead of falling back on the ORM to do the magic.

If performance is high on your list, I'd be reluctant to take a dependency on any ORM especially EF which is new on the scene and highly complex. ORM's speed up development (a little) but are going to make your SQL query performance hard to predict, and in most cases slower than hand rolled SQL/Stored Procs.

You can also unit test SQL/Stored Procs independently of the application and therefore isolate performance issues as either DB/query related or application related.

I guess you are using ADO.NET in your DAL already, so I'd suggest investing the time and effort in refactoring it rather than throwing it out.