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A database shard, or simply a shard, is a horizontal partition of data in a database or search engine. Each shard may be 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.
MySQL Cluster, also known as MySQL Ndb Cluster is a technology providing shared-nothing clustering and auto-sharding for the MySQL database management system.It is designed to provide high availability and high throughput with low latency, while allowing for near linear scalability. [3]
"if the database shard is based on some real-world segmentation of the data (e.g., European customers v. American customers)" -- From a relational data base view this example is more likely to be a vertical one rather than a horizontal one (unless the data is far from normalized).
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]
A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration , for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems.
The internal structure of the database should be unaffected by changes to the physical aspects of the storage: For example, a changeover to a new disk. The three levels are: External Level (User Views): A user's view of the database describes a part of the database that is relevant to a particular user. It excludes irrelevant data as well as ...
For example, Base One describes a database-centric distributed computing architecture for grid and cluster computing, and explains how this design provides enhanced security, fault-tolerance, and scalability. [4] an overall enterprise architecture that favors shared data models [5] over allowing each application to have its own, idiosyncratic ...
For example, in OLTP systems, many transactions may attempt to insert data into the same table at the same time. In a shared nothing system, at any given moment, all such inserts are processed by the single server that manages that partition (shard) of the table, possibly overwhelming it, while the rest of the system has little to do. Many such ...