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  2. Partition (database) - Wikipedia

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

    Database partitioning emerged in the 1980s with systems like Teradata and NonStop SQL. The approach was later adopted by NoSQL databases and Hadoop-based data warehouses. While implementations vary between transactional and analytical workloads, the core principles of partitioning remain consistent across both use cases. [1]

  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. MySQL Cluster - Wikipedia

    en.wikipedia.org/wiki/MySQL_Cluster

    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 ]

  5. MySQL - Wikipedia

    en.wikipedia.org/wiki/MySQL

    MySQL (/ ˌ m aɪ ˌ ɛ s ˌ k juː ˈ ɛ l /) [5] is an open-source relational database management system (RDBMS). [5] [6] Its name is a combination of "My", the name of co-founder Michael Widenius's daughter My, [7] and "SQL", the acronym for Structured Query Language.

  6. TimescaleDB - Wikipedia

    en.wikipedia.org/wiki/TimescaleDB

    TimescaleDB is an open-source time series database [3] [4] [5] developed by Timescale Inc. It is written in C and extends PostgreSQL. [6] [7] TimescaleDB is a relational database [8] and supports standard SQL queries. Additional SQL functions and table structures provide support for time series data oriented towards storage, performance, and ...

  7. PACELC theorem - Wikipedia

    en.wikipedia.org/wiki/PACELC_theorem

    The tradeoff between availability, consistency and latency, as described by the PACELC theorem. In database theory, the PACELC theorem is an extension to the CAP theorem.It states that in case of network partitioning (P) in a distributed computer system, one has to choose between availability (A) and consistency (C) (as per the CAP theorem), but else (E), even when the system is running ...

  8. CAP theorem - Wikipedia

    en.wikipedia.org/wiki/CAP_theorem

    The PACELC theorem, introduced in 2010, [8] builds on CAP by stating that even in the absence of partitioning, there is another trade-off between latency and consistency. PACELC means, if partition (P) happens, the trade-off is between availability (A) and consistency (C); Else (E), the trade-off is between latency (L) and consistency (C).

  9. Category:Data partitioning - Wikipedia

    en.wikipedia.org/wiki/Category:Data_partitioning

    Pages in category "Data partitioning" The following 8 pages are in this category, out of 8 total. This list may not reflect recent changes. ...