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  2. 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 ...

  3. Shared-nothing architecture - Wikipedia

    en.wikipedia.org/wiki/Shared-nothing_architecture

    In databases, a term for the part of a database on a single node is a shard. A SN system typically partitions its data among many nodes. A SN system typically partitions its data among many nodes. A refinement is to replicate commonly used but infrequently modified data across many nodes, allowing more requests to be resolved on a single node.

  4. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]

  5. Database virtualization - Wikipedia

    en.wikipedia.org/wiki/Database_Virtualization

    The act of partitioning data stores as a database grows has been in use for several decades. There are two primary ways that data has been partitioned inside legacy data management systems: Shared-data databases: an architecture that assumes all database cluster nodes share a single partition.

  6. Consensus clustering - Wikipedia

    en.wikipedia.org/wiki/Consensus_clustering

    Consensus clustering is a method of aggregating (potentially conflicting) results from multiple clustering algorithms.Also called cluster ensembles [1] or aggregation of clustering (or partitions), it refers to the situation in which a number of different (input) clusterings have been obtained for a particular dataset and it is desired to find a single (consensus) clustering which is a better ...

  7. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    When partitioning the data set into clusters, the medoid of each cluster can be used as a representative of each cluster. Clustering algorithms based on the idea of medoids include: Partitioning Around Medoids (PAM), the standard k-medoids algorithm; Hierarchical Clustering Around Medoids (HACAM), which uses medoids in hierarchical clustering

  8. Partition (database) - Wikipedia

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

    A partition is a division of a logical database or its constituent elements into distinct independent parts. 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]

  9. Comparison of OLAP servers - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_OLAP_servers

    Partitioning Usage Based Optimizations Load Balancing and Clustering Apache Doris Yes Yes Yes Yes ... Host authentication, database authentication, LDAP,