Glossary of Common Database Terms

Common Database Terms

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This glossary covers database terms and concepts used across all types of databases. It does not include terms specific to certain systems or databases.

ACID 

The ACID model of database design enforces data integrity through atomicity, consistency, isolation and durability:

  • Atomicity: Each database transaction must follow an all-or-nothing rule, meaning that if any part of the transaction fails, the entire transaction fails.
  • Consistency: Each database transaction must follow all the database's defined rules; any transaction that would violate these rules is not allowed.
  • Isolation: Each database transaction will occur independently of any other transaction. For example, if multiple transactions are submitted concurrently, the database will prevent any interference between them.
  • Durability: Each database transaction will permanently exist in any database failure, via backups or other means.

Attribute  

A database attribute is a characteristic of a database entity. Simply put, an attribute is the column in a database table, which itself is known as an entity.

Authentication

Databases use authentication to ensure that only authorized users can access the database, or certain aspects of the database. For example, administrators might be authorized to insert or edit data, while regular employees might be able to only view data.

Authentication is implemented with user names and passwords.

BASE Model

The BASE model has been developed as an alternative to the ACID model to serve the needs of noSQL databases in which the data is not structured in the same way required by relational databases. Its primary tenets are Basic Availability, Soft State and Eventual Consistency:

  • Basic Availability: The database is available and operational, backed sometimes by data replication distributed across several servers.
  • Soft State: Countering the ACID model of strict consistency, this tenet states that data does not always have to be consistent and that any enforced consistency is the responsibility of the individual database or developer.
  • Eventual Consistency: At some undefined, future point, the database will achieve consistency.

Constraints

A database constraint is a set of rules that define valid data. Multiple types of constraints exist. The primary constraints are:

  • Unique constraints: A field must contain a unique value in the table.
  • CHECK constraints: A field can contain only specific data types and even certain allowable values.
  • DEFAULT constraints: A field will contain a default value if it has no existing value; this eliminates a NULL value.
  • PRIMARY KEY Constraints: The primary key must be unique.
  • FOREIGN KEY Constraints: The foreign key must match an existing primary key in another table.

Database Management System (DBMS)

This is the software that manages all aspects of working with a database, from storing and securing the data to enforcing data integrity rules, to providing forms for data entry and manipulation.

A Relational Database Management System (RDBMS) implements the relational model of tables and relationships between them.

Entity

An entity is simply a table in a database. It is described using an Entity-Relationship Diagram, which is a type of graphic that shows the relationships between database tables.

Functional Dependency

A functional dependency constraint helps to ensure data validity, and exists when one attribute determines the value of another, described as A -> B which means that the value of A determines the value of B, or that B is "functionally dependent" on A. For example, a table in a university that includes records of all students might have a functional dependency between the student ID and the student name, i.e. the unique student ID will determine the value of the name.

Index

An index is a data structure that helps speed database queries for large data sets.

Database developers create an index on particular columns in a table. The index holds the column values but just pointers to the data in the rest of the table, and can be searched efficiently and quickly.

Key

A key is a database field whose purpose is to uniquely identify a record. Keys help enforce data integrity and avoid duplication. The main types of keys used in a database are candidate keys, primary keys foreign keys.

  • Candidate keys: The set of columns that can each uniquely identify a record and from which the primary key is chosen.
  • Primary keys: The key chosen to uniquely identify a record in a table. This key cannot be NULL.
  • Foreign keys: The key linking a record to a record in another table. A table's foreign key must exist as the primary key of another table.

Normalization

To normalize a database is to design its tables (relations) and columns (attributes) in a way to ensure data integrity and to avoid duplication. The primary levels of normalization are First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF) and Boyce-Codd Normal Form (BCNF). 

NoSQL

NoSQL is a database model developed to respond to the need for storing unstructured data such as emails, social media posts, video or images. Rather than using SQL and the strict ACID model to ensure data integrity, NoSQL follows the less-strict BASE model. A NoSQL database schema does not use tables to store data; rather, it might use a key/value design or graphs.

Null

The value NULL is frequently confused to mean "none" or zero; however, it actually means "unknown." If a field has a value of NULL, it is a placeholder for an unknown value. Structured Query Language (SQL) uses the IS NULL and IS NOT NULL operators to test for null values.

Query

A database query is how users interact with a database. It is usually written in SQL and can be either a select query or an action query. A select query requests data from a database; an action query changes, updates or adds data. Some databases provide forms that hide the semantics of the query, allowing users to easily request information without having to understand SQL.

Schema

A database schema is the design of tables, columns, relations and constraints that make up a database. Schemas are usually described using the SQL CREATE statement.

Stored Procedure

A stored procedure is a pre-compiled query, or SQL statement that can be shared across multiple programs and users in a Database Management System. Stored procedures improve efficiency, help enforce data integrity and boost productivity. 

Structured Query Language

Structured Query Language, or SQL, is the most commonly used language to access data from a database. The Data Manipulation Language (DML) contains the subset of SQL commands used most frequently and includes SELECT, INSERT, UPDATE and DELETE. 

Trigger

A trigger is a stored procedure set to execute given a particular event, usually a change to a table's data. For example, a trigger might be designed to write to a log, gather statistics or compute a value. 

View

A database view is a filtered set of data displayed to the end user in order to hide data complexity and streamline the user experience. A view can join data from two or more tables and contains a subset of information.