Abstract
Choosing proper datatypes to match the domain to satisfy logical modeling is an important task. One datatype might be more efficient than another of a similar type. For example, you can store integer data in an integer datatype, a numeric datatype, a floating point datatype, a character type, or even a binary column, but these datatypes certainly aren’t alike in implementation or performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Louis Davidson
About this chapter
Cite this chapter
Davidson, L., Moss, J. (2016). Scalar Datatype Reference. In: Pro SQL Server Relational Database Design and Implementation. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-1973-7_15
Download citation
DOI: https://doi.org/10.1007/978-1-4842-1973-7_15
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-1972-0
Online ISBN: 978-1-4842-1973-7
eBook Packages: Professional and Applied ComputingApress Access BooksProfessional and Applied Computing (R0)