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Virtual store research is an extension of the traditional methods of marketing research. [1] While marketing research employs techniques like focus groups, surveys and observation to better understand consumer decision-making, virtual store research uses these standard research techniques within a simulated store setting, delivered via computer.
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 ...
dBm or dB mW (decibel-milliwatts) is a unit of power level expressed using a logarithmic decibel (dB) scale respective to one milliwatt (mW). It is commonly used by radio, microwave and fiber-optical communication technicians & engineers to measure the power of system transmissions on a log scale , which can express both very large and very ...
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.
Virtual Storage Access Method (VSAM) [1] is an IBM direct-access storage device (DASD) file storage access method, first used in the OS/VS1, OS/VS2 Release 1 (SVS) and Release 2 (MVS) operating systems, later used throughout the Multiple Virtual Storage (MVS) architecture and now in z/OS.
The dbm library stores arbitrary data by use of a single key (a primary key) in fixed-size buckets and uses hashing techniques to enable fast retrieval of the data by key. The hashing scheme used is a form of extendible hashing , so that the hashing scheme expands as new buckets are added to the database, meaning that, when nearly empty, the ...
The origin of Ordered Key-Value Store stems from the work of Ken Thompson on dbm in 1979. Later in 1991, Berkeley DB was released that featured a B-Tree backend that allowed the keys to stay sorted. Berkeley DB was said to be very fast and made its way into various commercial product. It was included in Python standard library until 2.7. [1]
Berkeley DB 1.x releases focused on managing key/value data storage and are referred to as "Data Store" (DS). The 2.x releases added a locking system enabling concurrent access to data. This is what is known as "Concurrent Data Store" (CDS). The 3.x releases added a logging system for transactions and recovery, called "Transactional Data Store ...