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  2. Trino (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Trino_(SQL_query_engine)

    Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like HDFS, AWS S3, Google Cloud Storage, or Azure Blob Storage [4] using the Hive [2] and Iceberg [3 ...

  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. Query optimization - Wikipedia

    en.wikipedia.org/wiki/Query_optimization

    The set of query plans examined is formed by examining the possible access paths (e.g., primary index access, secondary index access, full file scan) and various relational table join techniques (e.g., merge join, hash join, product join). The search space can become quite large depending on the complexity of the SQL query. There are two types ...

  5. Database index - Wikipedia

    en.wikipedia.org/wiki/Database_index

    Covering indexes are each for a specific table. Queries which JOIN/ access across multiple tables, may potentially consider covering indexes on more than one of these tables. [7] A covering index can dramatically speed up data retrieval but may itself be large due to the additional keys, which slow down data insertion and update. To reduce such ...

  6. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical simulations. [1] As a result of these tradeoffs, row-oriented formats are more commonly used in Online transaction processing (OLTP) and column-oriented formats are more commonly used in Online analytical processing (OLAP).

  7. Comparison of MySQL database engines - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_MySQL...

    This is a comparison between notable database engines for the MySQL database management system (DBMS). A database engine (or "storage engine") is the underlying software component that a DBMS uses to create, read, update and delete (CRUD) data from a database.

  8. Comparison of relational database management systems - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_relational...

    Max DB size Max table size Max row size Max columns per row Max Blob/Clob size Max CHAR size Max NUMBER size Min DATE value Max DATE value Max column name size Informix Dynamic Server: ≈0.5 YB 12: ≈0,5YB 12: 32,765 bytes (exclusive of large objects) 32,765 4 TB 32,765 14: 10 125 13: 01/01/0001 10: 12/31/9999 128 bytes Ingres: Unlimited ...

  9. Table (database) - Wikipedia

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

    In a database, a table is a collection of related data organized in table format; consisting of columns and rows. In relational databases , and flat file databases , a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows , the cell being the unit where a row and column intersect ...