Rapidly Emerging Technology Series: Cloud Databases

The Rapidly Emerging Technology Series highlights current technologies that are relevant to data warehouse professionals.  This posting discusses cloud databases.

A growing trend in database systems is storing data in the cloud. The cloud metaphor is taken from the flowchart symbol of a cloud that represents data movement over the Internet (hence not visible to the flowchart….in the cloud).  Companies including Microsoft, Oracle, IBM and Amazon offer cloud storage services on vast server and storage complexes. 

Advantages of storing data with a cloud service is that they will perform all administrative services, replicate data on various severs for instantly available backups, and automatically scale growing databases and applications.  These services could result in considerable cost savings for some organizations.  Database development can be done without a large commitment to hardware purchases and administrative staff, and purchase and hiring decisions can be postponed for later assessment.

For example, Microsoft offers a product called SQL Azure which is a cloud-based SQL Server service.  SQL Azure makes it possible to store and access SQL Server data on cloud-based servers as well as integrate cloud and local data in a hybrid database.  SQL Azure databases can contain SQL Server tables, indexes, stored procedures, and other common database objects.

Cloud servers can be public or private.  A public cloud is a service purchased from a cloud services vendor.  A private cloud is set up by an organization with its own servers and storage.  A public cloud has the advantage of very sophisticated administrative and scaling capabilities that would be very complicated and expensive for smaller organizations to set up themselves.  A private cloud may be used when regulatory requirements are needed above and beyond the security provided by public clouds. 

A cloud hybrid database is one where data is stored on both cloud and local servers. This may be done for a number of reasons including replication of critical data on separate servers, separating processing of various data sources, providing separate access to various data marts, and other data distribution and access requirements.