Примери за използване на Dbmss на Английски и техните преводи на Български
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Many DBMSs divide their work into two levels according to the"Client-Server" architecture.
Most other DBMS implementations usually called relational are actually SQL DBMSs.
DBMSs are found at the heart of most database applications.
This in spite of the fact that tools may exist to help migration between specific DBMSs.
Some of them are much simpler than full-fledged DBMSs, with more elementary DBMS functionality.
Typically, a DBMS vendor provides tools to help importing databases from other popular DBMSs.
Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans.
Only in the mid-1980s did computing hardware become powerful enough to allow the wide deployment of relational systems(DBMSs plus applications).
Some DBMSs support specifying which character encoding was used to store data, so multiple encodings can be used in the same database.
It was not until the mid-1980s that computing hardware became powerful enough to allow relational systems(DBMSs plus applications) to be widely deployed.
The reasons are primarily economical(different DBMSs may have different total costs of ownership or TCOs), functional, and operational(different DBMSs may have different capabilities).
The standards have been regularly enhanced since and is supported(with varying degrees of conformance)by all mainstream commercial relational DBMSs.
Load Balancing: The transaction processing monitor can balance client requests across multiple DBMSs on one or more computers by directing client calls to the least loaded server.
A competing“next generation” known as NewSQLdatabases attempted new implementations that retained the relational/ SQL model while aiming to match the high performance of the DBMSs.
Database management systems frequently provide database server functionality, and some DBMSs(e.g., MySQL) rely exclusively on the client- server model for database access.
A competing"next generation" known as NewSQL databases attempted new implementations that retained the relational/SQL model while aiming to match the high performance of NoSQL compared to commercially available relational DBMSs.
DBMSs may be built around a custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions from databases before the inception of Structured Query Language(SQL).
With the progress in technology in the areas of processors, computer memory, computer storage and computer networks, the sizes, capabilities, andperformance of databases and their respective DBMSs have grown in orders of magnitudes.
According to the report, Gartner includes in its Leaders quadrant for data warehouse DBMSs"those vendors that demonstrate the greatest degree of support for data warehouses of all sizes, with large numbers of concurrent users and the management of mixed data warehousing workloads.
Database designers and database administrators interact with the DBMS through dedicated interfaces to build and maintain the applications' databases, and thus need some more knowledge andunderstanding about how DBMSs operate and the DBMSs' external interfaces and tuning parameters.
Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups: Data definition- Creation, modification and removal of definitions that define the organization of the data.
DBMSs may be built around a custom multitasking kernel with built-in networking support, but modern DBMSs typically rely on a standard operating system to provide these functions from databases before the inception of Structured Query Language(SQL).
Databases and DBMSs can be categorized according to the database model(s) that they support(such as relational or XML), the type(s) of computer they run on(from a server cluster to a mobile phone), the query language(s) used to access the database(such as SQL or XQuery), and their internal engineering, which affects performance, scalability, resilience, and security.