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Database scalability has three basic dimensions: amount of data, volume of requests and size of requests. Requests come in many sizes: transactions generally affect small amounts of data, but may approach thousands per second; analytic queries are generally fewer, but may access more data. A related concept is elasticity, the ability of a ...
A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard is held on a separate database server instance, to spread load. Some data within a database remains present in all shards, [a] but some appear only in a single shard. Each shard (or server) acts as the single source for this subset ...
Scalability is the property of a system to handle a growing amount of work. One definition for software systems specifies that this may be done by adding resources to the system. [1] In an economic context, a scalable business model implies that a company can increase sales given increased resources. For example, a package delivery system is ...
Scalability testing is the testing of a software application to measure its capability to scale up or scale out in terms of any of its non-functional capability. Performance, scalability and reliability testing are usually grouped together by software quality analysts . The main goals of scalability testing are to determine the user limit for ...
Due to increasing requirements for horizontal scalability and fault tolerance, NoSQL databases became prominent after 2009. NoSQL databases use a variety of data models, with document, graph, and key–value models being popular. [2] A multi-model database is a database that can store, index and query data in more than one model.
Autoscaling. Autoscaling, also spelled auto scaling or auto-scaling, and sometimes also called automatic scaling, is a method used in cloud computing that dynamically adjusts the amount of computational resources in a server farm - typically measured by the number of active servers - automatically based on the load on the farm.
Denormalization is a strategy used on a previously- normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data. [1][2] It is often motivated by ...
A relational database (RDB[1]) is a database based on the relational model of data, as proposed by E. F. Codd in 1970. [2] A database management system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems are equipped with the option of using SQL (Structured Query Language ...