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Outline of databases

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The following outline 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

History of databases

Database use

  • Database#Major database usage requirements
  • Database theory – encapsulates a broad range of topics related to the study and research of the theoretical realm of databases and database management systems.
  • Database model – the theoretical foundation of a database and fundamentally determines in which manner data can be stored, organized, and manipulated in a database system.
  • Database management system – (DBMS) is a software package with computer programs that control the creation, maintenance, and use of a database.
  • Database machine – or back end processor is a computer or special hardware that stores and retrieves data from a database.
  • Database server – computer program that provides database services to other computer programs or computers, as defined by the client–server model.
  • Database application – computer program whose primary purpose is entering and retrieving information from a computer-managed database.
  • Database connection – facility in computer science that allows client software to communicate with database server software, whether on the same machine or not.
    • datasource
    • Data Source Name – (DSN, sometimes known as a database source name though data sources are not limited to databases) are data structures used to describe a connection to a data source.
  • Database administrator – (short form DBA) is a person responsible for the installation, configuration, upgrade, administration, monitoring and maintenance of physical[clarification needed] databases.
  • Lock
  • Comparison of database tools –
  • Database-centric architecture – or data-centric architecture has several distinct meanings, generally relating to software architectures in which databases play a crucial role.
  • Intelligent database – was put forward as a system that manages information (rather than data) in a way that appears natural to users and which goes beyond simple record keeping.
  • Two-phase locking – (2PL) is a concurrency control method that guarantees serializability.
  • Locks with ordered sharing – comprises several variants of the Two phase locking (2PL) concurrency control protocol generated by changing the blocking semantics of locks upon conflicts.
  • Load file – in the litigation community is commonly referred to as the file used to import data (coded, captured or extracted data from ESI processing) into a database; or the file used to link images.
  • Database publishing – an area of automated media production in which specialized techniques are used to generate paginated documents from source data residing in traditional databases.
  • Halloween Problem – a phenomenon in databases in which an update operation causes a change in the physical ___location of a row, potentially allowing the row to be visited more than once during the operation.
  • Log shipping – the process of automating the backup of a database and transaction log files on a primary (production) database server, and then restoring them onto a standby server.

Database languages

Database languages

Database security

Database security

  • Database activity monitoring – (DAM) is a 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 – , in Credit Card terms, refers to a list of Credit Card owners who chargeback a lot.

Database design

Database design

  • Entity-relationship model – (ER model for short) is an abstract and conceptual representation of data.
  • Database normalization – the 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 – an 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 – an 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

  • Database model
  • Database normalization
  • Database storage structures –
  • Distributed database management system –
  • Federated database system – type of meta-database management system (DBMS), which transparently maps multiple autonomous database systems into a single federated database.
  • Referential integrity – .
  • Relational algebra – , an offshoot of first-order logic (and of algebra of sets), deals with a set of finitary relations (see also relation (database)) that is closed under certain operators.
  • Relational calculus – consists of two calculi, the tuple relational calculus and the ___domain relational calculus, that are part of the relational model for databases and provide a declarative way to specify database queries.
  • Relational database – collection of data items organized as a set of formally-described tables from which data can be accessed easily.
  • Relational database management system – (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by E.
  • Relational model – for database management is a database model based on first-order logic|first-order predicate logic, first formulated and proposed in 1969 by Edgar F.
  • 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.
  • Transaction processing –

Concepts

  • Database – an 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 – candidate key of a relation is a minimal superkey for that relation; that is, a set of attributes such that
  • Foreign key – referential constraint between two tables.
  • Primary key
  • Superkey – defined in the relational model of database organization as a 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 – in a database is a unique identifier for either an entity in the modeled world or an object in the database.
  • Armstrong's axioms – are a set of axioms (or, more precisely, inference rules) used to infer all the functional dependencies on a relational database.
  • NoSQL – NoSQL is a 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 – , or metadata repository, 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.
  • Java Database Connectivity – .
  • Open Database Connectivity
  • Query language
  • Query optimizer – the component of a database management system that attempts to determine the most efficient way to execute a query.
  • Query plan – (or query execution plan) is an ordered set of steps used to access or modify information in a SQL relational database management system.

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 – (or "ODS") is a 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 – (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), is the process that results in the discovery of new patterns in large data sets.
  • 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

  • Bill Inmon –
  • Ralph Kimball – (Born 1944) is an author on the subject of data warehousing and business intelligence.

Products


  • Ling Liu and Tamer M. Özsu (Eds.) (2009). "Encyclopedia of Database Systems, 4100 p. 60 illus. ISBN 978-0-387-49616-0. Table of Content available at http://refworks.springer.com/mrw/index.php?id=1217
  • Beynon-Davies, P. (2004). Database Systems. 3rd Edition. Palgrave, Houndmills, Basingstoke.
  • Connolly, Thomas and Carolyn Begg. Database Systems. New York: Harlow, 2002.
  • Date, C. J. (2003). An Introduction to Database Systems, Fifth Edition. Addison Wesley. ISBN 0-201-51381-1. {{cite book}}: Invalid |ref=harv (help)
  • Gray, J. and Reuter, A. Transaction Processing: Concepts and Techniques, 1st edition, Morgan Kaufmann Publishers, 1992.
  • Kroenke, David M. and David J. Auer. Database Concepts. 3rd ed. New York: Prentice, 2007.
  • Lightstone, S.; Teorey, T.; Nadeau, T. (2007). Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more. Morgan Kaufmann Press. ISBN 0-12-369389-6. {{cite book}}: Invalid |ref=harv (help)
  • Teorey, T.; Lightstone, S. and Nadeau, T. Database Modeling & Design: Logical Design, 4th edition, Morgan Kaufmann Press, 2005. ISBN 0-12-685352-5

Persons influential in databases

See also

References

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