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  2. Database scalability - Wikipedia

    en.wikipedia.org/wiki/Database_scalability

    Database scalability is the ability of a database to handle changing demands by adding/removing resources. Databases use a host of techniques to cope. [ 1 ] According to Marc Brooker: "a system is scalable in the range where marginal cost of additional workload is nearly constant."

  3. Shard (database architecture) - Wikipedia

    en.wikipedia.org/wiki/Shard_(database_architecture)

    Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...

  4. Scalability - Wikipedia

    en.wikipedia.org/wiki/Scalability

    Webscale is a computer architectural approach that brings the capabilities of large-scale cloud computing companies into enterprise data centers. [ 4 ] In distributed systems , there are several definitions according to the authors, some considering the concepts of scalability a sub-part of elasticity , others as being distinct.

  5. Multi-model database - Wikipedia

    en.wikipedia.org/wiki/Multi-model_database

    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.

  6. Scalability testing - Wikipedia

    en.wikipedia.org/wiki/Scalability_testing

    Vertical scaling, also known as scaling up, is the process of replacing a component with a device that is generally more powerful or improved. For example, replacing a processor with a faster one. Horizontal scaling, also known as scaling out is setting up another server for example to run in parallel with the original so they share the workload.

  7. Entity–attribute–value model - Wikipedia

    en.wikipedia.org/wiki/Entity–attribute–value...

    An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design.

  8. Partition (database) - Wikipedia

    en.wikipedia.org/wiki/Partition_(database)

    Database partitioning refers to intentionally breaking a large database into smaller ones for scalability purposes, distinct from network partitions which are a type of network fault between nodes. [1] In a partitioned database, each piece of data belongs to exactly one partition, effectively making each partition a small database of its own. [1]

  9. Very large database - Wikipedia

    en.wikipedia.org/wiki/Very_large_database

    A very large database, (originally written very large data base) or VLDB, [1] is a database that contains a very large amount of data, so much that it can require specialized architectural, management, processing and maintenance methodologies.