Outline of databases

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

Contents

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

Database security

Database security

Database design

Database design

Database programming

Database management

Database management systems

Database management system

Concepts

Objects

Components

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

Products

Database scholars

See also

Related Research Articles

<span class="mw-page-title-main">Database</span> Organized collection of data in computing

In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a database system. Often the term "database" is also used loosely to refer to any of the DBMS, the database system or an application associated with the database.

<span class="mw-page-title-main">Object database</span> Type of database management system

An object database or object-oriented database is a database management system in which information is represented in the form of objects as used in object-oriented programming. Object databases are different from relational databases which are table-oriented. A third type, object–relational databases, is a hybrid of both approaches. Object databases have been considered since the early 1980s.

A relational database is a database based on the relational model of data, as proposed by E. F. Codd in 1970. A system used to maintain relational databases is a relational database management system (RDBMS). Many relational database systems are equipped with the option of using SQL for querying and updating the database.

The relational model (RM) is an approach to managing data using a structure and language consistent with first-order predicate logic, first described in 1969 by English computer scientist Edgar F. Codd, where all data is represented in terms of tuples, grouped into relations. A database organized in terms of the relational model is a relational database.

Structured Query Language (SQL) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS). It is particularly useful in handling structured data, i.e., data incorporating relations among entities and variables.

<span class="mw-page-title-main">Object–relational database</span> Database management system

An object–relational database (ORD), or object–relational database management system (ORDBMS), is a database management system (DBMS) similar to a relational database, but with an object-oriented database model: objects, classes and inheritance are directly supported in database schemas and in the query language. In addition, just as with pure relational systems, it supports extension of the data model with custom data types and methods.

<span class="mw-page-title-main">Data model</span> Model that organizes elements of data and how they relate to one another and to real-world entities.

A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.

<span class="mw-page-title-main">IBM Db2</span> Relational model database server

Db2 is a family of data management products, including database servers, developed by IBM. It initially supported the relational model, but was extended to support object–relational features and non-relational structures like JSON and XML. The brand name was originally styled as DB/2, then DB2 until 2017 and finally changed to its present form.

Online analytical processing, or OLAP, is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas, with new applications emerging, such as agriculture.

In the context of SQL, data definition or data description language (DDL) is a syntax for creating and modifying database objects such as tables, indices, and users. DDL statements are similar to a computer programming language for defining data structures, especially database schemas. Common examples of DDL statements include CREATE, ALTER, and DROP.

IMAGE is a database management system (DBMS) developed by Hewlett-Packard and included with the HP 3000 minicomputer. It was the primary reason for that platform's success in the market. It was also sometimes referred to as IMAGE/3000 in its initial release, and later versions were known as TurboIMAGE, and TurboIMAGE/XL after the PA-RISC migration.

In a database, a view is the result set of a stored query, which can be queried in the same manner as a persistent database collection object. This pre-established query command is kept in the data dictionary. Unlike ordinary base tables in a relational database, a view does not form part of the physical schema: as a result set, it is a virtual table computed or collated dynamically from data in the database when access to that view is requested. Changes applied to the data in a relevant underlying table are reflected in the data shown in subsequent invocations of the view.

Object–relational impedance mismatch creates difficulties going from data in relational data stores to usage in domain-driven object models. Object-orientation (OO) is the default method for business-centric design in programming languages. The problem lies in neither relational nor OO, but in the conceptual difficulty mapping between the two logic models. Both are logical models implementable differently on database servers, programming languages, design patterns, or other technologies. Issues range from application to enterprise scale, whenever stored relational data is used in domain-driven object models, and vice versa. Object-oriented data stores can trade this problem for other implementation difficulties.

An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design. The use-case targets applications which offer a large or rich system of defined property types, which are in turn appropriate to a wide set of entities, but where typically only a small, specific selection of these are instantiated for a given entity. Therefore, this type of data model relates to the mathematical notion of a sparse matrix.

<span class="mw-page-title-main">Database model</span> Type of data model

A database model is a type of data model that determines the logical structure of a database. It fundamentally determines in which manner data can be stored, organized and manipulated. The most popular example of a database model is the relational model, which uses a table-based format.

A document-oriented database, or document store, is a computer program and data storage system designed for storing, retrieving and managing document-oriented information, also known as semi-structured data.

NoSQL is an approach to database design that focuses on providing a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Instead of the typical tabular structure of a relational database, NoSQL databases house data within one data structure. Since this non-relational database design does not require a schema, it offers rapid scalability to manage large and typically unstructured data sets. NoSQL systems are also sometimes called "Not only SQL" to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures.

rasdaman Database management system

rasdaman is an Array DBMS, that is: a Database Management System which adds capabilities for storage and retrieval of massive multi-dimensional arrays, such as sensor, image, simulation, and statistics data. A frequently used synonym to arrays is raster data, such as in 2-D raster graphics; this actually has motivated the name rasdaman. However, rasdaman has no limitation in the number of dimensions - it can serve, for example, 1-D measurement data, 2-D satellite imagery, 3-D x/y/t image time series and x/y/z exploration data, 4-D ocean and climate data, and even beyond spatio-temporal dimensions.

<span class="mw-page-title-main">Array DBMS</span> System that provides database services specifically for arrays

An array database management system or array DBMS provides database services specifically for arrays, that is: homogeneous collections of data items, sitting on a regular grid of one, two, or more dimensions. Often arrays are used to represent sensor, simulation, image, or statistics data. Such arrays tend to be Big Data, with single objects frequently ranging into Terabyte and soon Petabyte sizes; for example, today's earth and space observation archives typically grow by Terabytes a day. Array databases aim at offering flexible, scalable storage and retrieval on this information category.

<span class="mw-page-title-main">SingleStore</span>

SingleStore is a proprietary, cloud-native database designed for data-intensive applications. A distributed, relational, SQL database management system (RDBMS) that features ANSI SQL support, it is known for speed in data ingest, transaction processing, and query processing.

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