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A glossary of terms for Database Administrators

3 min read
Published on 7th August 2023
  • ACID: An acronym for Atomicity, Consistency, Isolation, Durability, these properties ensure reliable processing in a database system.

  • BASE: An acronym for Basic Availability, Soft State, Eventual Consistency, these properties are followed in a distributed database system.

  • Data Normalization: The process of organizing data in a database to reduce redundancy and improve data integrity.

  • DML (Data Manipulation Language): A language that enables users to access or manipulate data, such as SQL's SELECT, INSERT, UPDATE, and DELETE commands.

  • DDL (Data Definition Language): A language that defines data structures. In SQL, the DDL includes the CREATE, ALTER, and DROP commands.

  • Primary Key: A unique identifier for a database record.

  • Foreign Key: A set of one or more columns used to establish a link between the data in two tables.

  • Index: A data structure that improves the speed of data retrieval operations on a database table.

  • View: A virtual or logical table composed from the result set of a query.

  • Stored Procedure: A set of SQL statements with an assigned name, stored in the database for reuse.

  • Trigger: A stored procedure that automatically performs an action when a specific operation, such as changing data in a table, occurs.

  • Cursor: A database control structure that enables traversal over the records in a database.

  • OLAP (Online Analytical Processing): A category of software tools that analyze data stored in databases and provide a multi-dimensional analytical view of data.

  • OLTP (Online Transaction Processing): A class of software applications capable of supporting transaction-oriented programs.

  • Entity-Relationship Diagram (ERD): A data modeling technique that visually represents an information system's entities and the relationships between them.

  • Join: A method of linking rows between two or more tables based on related columns.

  • Sharding: The process of storing data records across multiple machines to manage large amounts of data and load.

  • Replication: The process of sharing data across multiple databases to ensure consistency.

  • Backup and Recovery: Procedures to create and store copies of data that can be used to protect an organization against data loss.

  • Normalization: The process of designing a database in an efficient manner by eliminating redundant data.

  • Denormalization: The process of combining tables to improve read performance at the expense of some write performance.

  • Partitioning: The process of dividing a database into smaller parts (partitions) to manage and access data more efficiently.

  • Query Optimization: The process of choosing the most efficient means of executing a SQL statement.