C# – Linq and DataSetExtensions warnings using .NET Framework 2.0 and C# 3

LINQ to SQL only supports 1 to 1 mapping of database tables, views, sprocs and functions available in Microsoft SQL Server. It's a great API to use for quick data access construction to relatively well designed SQL Server databases. LINQ2SQL was first released with C# 3.0 and .Net Framework 3.5.

LINQ to Entities (ADO.Net Entity Framework) is an ORM (Object Relational Mapper) API which allows for a broad definition of object domain models and their relationships to many different ADO.Net data providers. As such, you can mix and match a number of different database vendors, application servers or protocols to design an aggregated mash-up of objects which are constructed from a variety of tables, sources, services, etc. ADO.Net Framework was released with the .Net Framework 3.5 SP1.

This is a good introductory article on MSDN: Introducing LINQ to Relational Data

float and double are floating binary point types. In other words, they represent a number like this:

10001.10010110011

The binary number and the location of the binary point are both encoded within the value.

decimal is a floating decimal point type. In other words, they represent a number like this:

12345.65789

Again, the number and the location of the decimal point are both encoded within the value – that's what makes decimal still a floating point type instead of a fixed point type.

The important thing to note is that humans are used to representing non-integers in a decimal form, and expect exact results in decimal representations; not all decimal numbers are exactly representable in binary floating point – 0.1, for example – so if you use a binary floating point value you'll actually get an approximation to 0.1. You'll still get approximations when using a floating decimal point as well – the result of dividing 1 by 3 can't be exactly represented, for example.

As for what to use when:

• For values which are "naturally exact decimals" it's good to use decimal. This is usually suitable for any concepts invented by humans: financial values are the most obvious example, but there are others too. Consider the score given to divers or ice skaters, for example.

• For values which are more artefacts of nature which can't really be measured exactly anyway, float/double are more appropriate. For example, scientific data would usually be represented in this form. Here, the original values won't be "decimally accurate" to start with, so it's not important for the expected results to maintain the "decimal accuracy". Floating binary point types are much faster to work with than decimals.