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Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located, [1] and can provide a single customer view (or single view of any other entity) of the overall data.
Virtualization of the database layer enables a shift away from the physical, toward the logical or virtual. Virtualization enables compute and storage resources to be pooled and allocated on demand. This enables both the sharing of single server resources for multi-tenancy, as well as the pooling of server resources into a single logical ...
A virtual private database or VPD masks data in a larger database so that only a subset of the data appears to exist, without actually segregating data into different tables, schemas or databases.
A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider.
A virtual environment is a networked application that allows a user to interact with both the computing environment and the work of other users. Email, chat, and web-based document sharing applications are all examples of virtual environments. Simply put, it is a networked common operating space.
A virtual machine implements functionality of a (physical) computer with an operating system. The software or firmware that creates a virtual machine on the host hardware is called a hypervisor or virtual machine monitor. [2] Software executed on these virtual machines is separated from the underlying hardware resources.
A database engine (or storage engine) is the underlying software component that a database management system (DBMS) uses to create, read, update and delete (CRUD) data from a database.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...