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Symmetric and antisymmetric relations. By definition, a nonempty relation cannot be both symmetric and asymmetric (where if a is related to b, then b cannot be related to a (in the same way)). However, a relation can be neither symmetric nor asymmetric, which is the case for "is less than or equal to" and "preys on").
In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.
In computer science, in particular in concurrency theory, a dependency relation is a binary relation on a finite domain , [1]: 4 symmetric, and reflexive; [1]: 6 i.e. a finite tolerance relation. That is, it is a finite set of ordered pairs, such that
A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring or releasing a lock, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included ...
In database theory, a relation, as originally defined by E. F. Codd, [1] is a set of tuples (d 1,d 2,...,d n), where each element d j is a member of D j, a data domain. Codd's original definition notwithstanding, and contrary to the usual definition in mathematics, there is no ordering to the elements of the tuples of a relation.
A data processing unit (DPU) is a programmable computer processor that tightly integrates a general-purpose CPU with network interface hardware. [1] Sometimes they are called "IPUs" (for "infrastructure processing unit") or "SmartNICs". [ 2 ]
"Data hierarchy" is a basic concept in data and database theory and helps to show the relationships between smaller and larger components in a database or data file. It is used to give a better sense of understanding about the components of data and how they are related.
The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, [1] [2] where all data are represented in terms of tuples, grouped into relations.