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  2. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    Data orientation is the representation of tabular data in a linear memory model such as in-disk or in-memory.The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...

  3. List of column-oriented DBMSes - Wikipedia

    en.wikipedia.org/wiki/List_of_column-oriented_DBMSes

    Time series database: Greenplum Database C Support and extensions available from VMware. MapD: C++ MariaDB ColumnStore C & C++ Formerly Calpont InfiniDB: Metakit: C++ MonetDB: C Open-source (since 2004) columnar Relational DBMS pioneer PostgreSQL cstore fdw, [1] vops [2] C cstore_fdw uses ORC format StarRocks Java & C++

  4. Database storage structures - Wikipedia

    en.wikipedia.org/wiki/Database_storage_structures

    By contrast, column-oriented DBMS store all data from a given column together in order to more quickly serve data warehouse-style queries. Correlation databases are similar to row-based databases, but apply a layer of indirection to map multiple instances of the same value to the same numerical identifier.

  5. C-Store - Wikipedia

    en.wikipedia.org/wiki/C-Store

    C-Store is a database management system (DBMS) based on a column-oriented DBMS developed by a team at Brown University, Brandeis University, Massachusetts Institute of Technology and the University of Massachusetts Boston including Michael Stonebraker, Stanley Zdonik, and Samuel Madden.

  6. Apache ORC - Wikipedia

    en.wikipedia.org/wiki/Apache_ORC

    Apache ORC (Optimized Row Columnar) is a free and open-source column-oriented data storage format. [3] It is similar to the other columnar-storage file formats available in the Hadoop ecosystem such as RCFile and Parquet. It is used by most of the data processing frameworks Apache Spark, Apache Hive, Apache Flink, and Apache Hadoop.

  7. List of in-memory databases - Wikipedia

    en.wikipedia.org/wiki/List_of_in-memory_databases

    SAP HANA, short for 'High Performance Analytic Appliance' is an in-memory, column-oriented, relational database management system written in C, C++: solidDB: Unicom Global 1992 Proprietary Relational with standard SQL support. ODBC and JDBC interfaces. Includes in-memory and on-disk tables in the same engine. Supports high availability. SQL CE

  8. Apache Parquet - Wikipedia

    en.wikipedia.org/wiki/Apache_Parquet

    Apache Parquet is a free and open-source column-oriented data storage format in the Apache Hadoop ecosystem. It is similar to RCFile and ORC, the other columnar-storage file formats in Hadoop, and is compatible with most of the data processing frameworks around Hadoop.

  9. Wide-column store - Wikipedia

    en.wikipedia.org/wiki/Wide-column_store

    A wide-column store (or extensible record store) is a type of NoSQL database. [1] It uses tables, rows, and columns, but unlike a relational database, the names and format of the columns can vary from row to row in the same table. A wide-column store can be interpreted as a two-dimensional key–value store. [1]