Outline of databases

The following is provided as an overview of and topical guide to databases:

Database – organized collection of data, today typically in digital form. The data are typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies).

What type of things are databases?

Databases can be described as all of the following:

Types of databases

History of databases

Database use

Database languages

Database languages –

  • Data definition language –
  • Data manipulation language –
  • Query language –
    • Information retrieval query language – query language used to make queries into database, where the semantics of the query are defined not by a precise rendering of a formal syntax, but by an interpretation of the most suitable results of the query.
    • SQL (Structured Query Language) – special-purpose programming language designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
    • XQuery – a query and functional programming language that queries and transforms collections of structured and unstructured data.

Database security

Database security –

  • Database activity monitoring (DAM) – database security technology for monitoring and analyzing database activity that operates independently of the database management system (DBMS) and does not rely on any form of native (DBMS-resident) auditing or native logs such as trace or transaction logs.
  • Database audit –
  • Database forensics – branch of digital forensic science relating to the forensic study of databases and their related metadata.
  • Negative database – credit card terminology for a list of credit card owners who chargeback a lot.

Database design

Database design –

  • Entity–relationship model (ER model) – abstract and conceptual representation of data.
  • Database normalization – process of organizing the fields and tables of a relational database to minimize redundancy and dependency.
  • Database refactoring – simple change to a database schema that improves its design while retaining both its behavioral and informational semantics.

Database programming

  • Database abstraction layer – application programming interface which unifies the communication between a computer application and databases such as SQL Server, DB2, MySQL, PostgreSQL, Oracle or SQLite.
  • Object–relational mapping (ORM, O/RM, and O/R mapping) – in computer software is a programming technique for converting data between incompatible type systems in object-oriented programming languages.

Database management

  • Database virtualization – it is the decoupling of the database layer, which lies between the storage and application layers within the application stack.
  • Database tuning – describes a group of activities used to optimize and homogenize the performance of a database.
    • Database caching – effective approach to achieve high scalability and performance.
  • Data migration § Database migration –
  • Database preservation – usually involves converting the information stored in a database, without losing the characteristics (Context, Content, Structure, Appearance and Behaviour) of the data, to a format which can be used in the long term, even if the technology and daily life knowledge changes.
  • Database integrity – ensures that data entered into the database is accurate, valid, and consistent.

Database management systems

Database management system –

Concepts

  • Database – organized collection of data, today typically in digital form.
  • ACID – (atomicity, consistency, isolation, durability) is a set of properties that guarantee that database transactions are processed reliably.
  • Create, read, update and delete (CRUD) – are the four basic functions of persistent storage.
  • Null –
  • Candidate key – minimal superkey for a relation.
  • Foreign key – referential constraint between two tables.
  • Primary key –
  • Superkey – set of attributes of a relation variable for which it holds that in all relations assigned to that variable, there are no two distinct tuples (rows) that have the same values for the attributes in this set.
  • Surrogate key – unique identifier in a database for either an entity in the modeled world or an object in the database.
  • Armstrong's axioms – set of axioms (or, more precisely, inference rules) used to infer all the functional dependencies on a relational database.
  • NoSQL – class of database management system identified by its non-adherence to the widely used relational database management system (RDBMS) model:

Objects

Components

  • Concurrency control – ensures that correct results for concurrent operations are generated, while getting those results as quickly as possible.
  • Data dictionary – as defined in the IBM Dictionary of Computing, is a "centralized repository of information about data such as meaning, relationships to other data, origin, usage, and format." Also called a "metadata repository".
  • Java Database Connectivity – .
  • Open Database Connectivity –
  • Query language –
  • Query optimizer – component of a database management system that attempts to determine the most efficient way to execute a query.
  • Query plan – ordered set of steps used to access or modify information in a SQL relational database management system. Also called a "query execution plan".

Functions

Database products

Database models

Models

Other models

Implementations

Data warehouse

Data warehouse –

Creating the data warehouse

Concepts

Variants

  • Anchor Modeling –
  • Column-oriented DBMS – database management system (DBMS) that stores data tables as sections of columns of data rather than as rows of data, like most relational DBMSs.
  • Data Vault Modeling –
  • HOLAP –
  • MOLAP – stands for Multidimensional Online Analytical Processing.
  • ROLAP – stands for Relational Online Analytical Processing.
  • Operational data store (ODS) – database designed to integrate data from multiple sources for additional operations on the data.

Elements

Fact

Dimension

Filling

Using the data warehouse

Concepts

  • Business intelligence (BI) – is defined as the ability for an organization to take all its capabilities and convert them into knowledge, ultimately, getting the right information to the right people, at the right time, via the right channel.
  • Dashboard –
  • Data mining – is the process that results in the discovery of new patterns in large data sets. It is the analysis step of the "Knowledge Discovery in Databases" process, or KDD.
  • Decision support system (DSS) –
  • OLAP cube – set of data, organized in a way that facilitates non-predetermined queries for aggregated information, or in other words, online analytical processing.

Languages

Tools

People

  • Edgar F. Codd – English Computer scientist who introduced the relational database model
  • Bill Inmon –
  • Ralph Kimball (Born 1944) – author on the subject of data warehousing and business intelligence.

Products

Database scholars

See also

References