Data Base

Data base

Database

"Database Software" redirects here. For the computer program, see Europress.
For a topical guide to this subject, see Outline of databases.
An example of output from an SQL database query.
A database is an organized collection ofdata.[1] A relational database, on the other hand, is a collection of schemas, tables,queries, reports, views, and other elements. Database designers typically organize the data to model aspects of reality in a way that supports processes requiring information, such as (for example) modelling the availability of rooms in hotels in a way that supports finding a hotel with vacancies.
A database-management system (DBMS) is acomputer-software application that interacts with end-users, other applications, and the database itself to capture and analyze data. A general-purpose DBMS allows the definition, creation, querying, update, and administration of databases. Well-known DBMSs includeMySQL, PostgreSQL, EnterpriseDB, MongoDB,MariaDB, Microsoft SQL Server, Oracle,Sybase, SAP HANA, MemSQL, SQLite and IBM DB2.
A database is not generally portable across different DBMSs, but different DBMSs can interoperate by using standards such as SQLand ODBC or JDBC to allow a single application to work with more than one DBMS. Computer scientists may classify database-management systems according to the database models that they support; the most popular database systems since the 1980s have all supported the relational model- generally associated with the SQLlanguage.[disputed ] Sometimes a DBMS is loosely referred to as a "database".

Terminology and overviewEdit

Formally, a "database" refers to a set of related data and the way it is organized. Access to this data is usually provided by a "database management system" (DBMS) consisting of an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized.
Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it.
Outside the world of professional information technology, the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index). This article is concerned only with databases where the size and usage requirements necessitate use of a database management system.[2]
Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups:
  • Data definition – Creation, modification and removal of definitions that define the organization of the data.
  • Update – Insertion, modification, and deletion of the actual data.[3]
  • Retrieval – Providing information in a form directly usable or for further processing by other applications. The retrieved data may be made available in a form basically the same as it is stored in the database or in a new form obtained by altering or combining existing data from the database.[4]
  • Administration – Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure.[5]
Both a database and its DBMS conform to the principles of a particular database model.[6]"Database system" refers collectively to the database model, database management system, and database.[7]
Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessorcomputers, with generous memory and RAIDdisk arrays used for stable storage. RAID is used for recovery of data if any of the disks fail. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large volume transaction processing environments. DBMSs are found at the heart of most database applications. DBMSs may be built around a custom multitasking kernel with built-innetworking support, but modern DBMSs typically rely on a standard operating systemto provide these functions.
Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans.[8]
Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance,scalability, resilience, and security.

ApplicationsEdit

Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see Enterprise software).
Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples of database applications include computerized library systems, flight reservation systems, computerized parts inventory systems, and many content management systems that store websites as collections of webpages in a database.

General-purpose and special-purpose DBMSsEdit

DBMS may become a complex software system and its development typically requires thousands of human years of development effort.[a] Some general-purpose DBMSs such as Adabas, Oracle and DB2 have been upgraded since the 1970s. General-purpose DBMSs aim to meet the needs of as many applications as possible, which adds to the complexity. However, since their development cost can be spread over a large number of users, they are often the most cost-effective approach. On the other hand, a general-purpose DBMS may introduce unnecessary overhead. Therefore, many systems use a special-purpose DBMS. A common example is an email system that performs many of the functions of a general-purpose DBMS such as the insertion and deletion of messages composed of various items of data or associating messages with a particular email address; but these functions are limited to what is required to handle email and don't provide the user with all of the functionality that would be available using a general-purpose DBMS.
Application software can often access a database on behalf of end-users, without exposing the DBMS interface directly. Application programmers may use a wire protocol directly, or more likely through anapplication programming interface. Database designers and database administrators interact with the DBMS through dedicated interfaces to build and maintain the applications' databases, and thus need some more knowledge and understanding about how DBMSs operate and the DBMSs' external interfaces and tuning parameters.

"Database Software" redirects here. For the computer program, see Europress.
For a topical guide to this subject, see Outline of databases.
An example of output from an SQL database query.
A database is an organized collection ofdata.[1] A relational database, on the other hand, is a collection of schemas, tables,queries, reports, views, and other elements. Database designers typically organize the data to model aspects of reality in a way that supports processes requiring information, such as (for example) modelling the availability of rooms in hotels in a way that supports finding a hotel with vacancies.
A database-management system (DBMS) is acomputer-software application that interacts with end-users, other applications, and the database itself to capture and analyze data. A general-purpose DBMS allows the definition, creation, querying, update, and administration of databases. Well-known DBMSs includeMySQL, PostgreSQL, EnterpriseDB, MongoDB,MariaDB, Microsoft SQL Server, Oracle,Sybase, SAP HANA, MemSQL, SQLite and IBM DB2.
A database is not generally portable across different DBMSs, but different DBMSs can interoperate by using standards such as SQLand ODBC or JDBC to allow a single application to work with more than one DBMS. Computer scientists may classify database-management systems according to the database models that they support; the most popular database systems since the 1980s have all supported the relational model- generally associated with the SQLlanguage.[disputed ] Sometimes a DBMS is loosely referred to as a "database".

Terminology and overviewEdit

Formally, a "database" refers to a set of related data and the way it is organized. Access to this data is usually provided by a "database management system" (DBMS) consisting of an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data). The DBMS provides various functions that allow entry, storage and retrieval of large quantities of information and provides ways to manage how that information is organized.
Because of the close relationship between them, the term "database" is often used casually to refer to both a database and the DBMS used to manipulate it.
Outside the world of professional information technology, the term database is often used to refer to any collection of related data (such as a spreadsheet or a card index). This article is concerned only with databases where the size and usage requirements necessitate use of a database management system.[2]
Existing DBMSs provide various functions that allow management of a database and its data which can be classified into four main functional groups:
  • Data definition – Creation, modification and removal of definitions that define the organization of the data.
  • Update – Insertion, modification, and deletion of the actual data.[3]
  • Retrieval – Providing information in a form directly usable or for further processing by other applications. The retrieved data may be made available in a form basically the same as it is stored in the database or in a new form obtained by altering or combining existing data from the database.[4]
  • Administration – Registering and monitoring users, enforcing data security, monitoring performance, maintaining data integrity, dealing with concurrency control, and recovering information that has been corrupted by some event such as an unexpected system failure.[5]
Both a database and its DBMS conform to the principles of a particular database model.[6]"Database system" refers collectively to the database model, database management system, and database.[7]
Physically, database servers are dedicated computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessorcomputers, with generous memory and RAIDdisk arrays used for stable storage. RAID is used for recovery of data if any of the disks fail. Hardware database accelerators, connected to one or more servers via a high-speed channel, are also used in large volume transaction processing environments. DBMSs are found at the heart of most database applications. DBMSs may be built around a custom multitasking kernel with built-innetworking support, but modern DBMSs typically rely on a standard operating systemto provide these functions.
Since DBMSs comprise a significant market, computer and storage vendors often take into account DBMS requirements in their own development plans.[8]
Databases and DBMSs can be categorized according to the database model(s) that they support (such as relational or XML), the type(s) of computer they run on (from a server cluster to a mobile phone), the query language(s) used to access the database (such as SQL or XQuery), and their internal engineering, which affects performance,scalability, resilience, and security.

ApplicationsEdit

Databases are used to support internal operations of organizations and to underpin online interactions with customers and suppliers (see Enterprise software).
Databases are used to hold administrative information and more specialized data, such as engineering data or economic models. Examples of database applications include computerized library systems, flight reservation systems, computerized parts inventory systems, and many content management systems that store websites as collections of webpages in a database.

General-purpose and special-purpose DBMSsEdit

DBMS may become a complex software system and its development typically requires thousands of human years of development effort.[a] Some general-purpose DBMSs such as Adabas, Oracle and DB2 have been upgraded since the 1970s. General-purpose DBMSs aim to meet the needs of as many applications as possible, which adds to the complexity. However, since their development cost can be spread over a large number of users, they are often the most cost-effective approach. On the other hand, a general-purpose DBMS may introduce unnecessary overhead. Therefore, many systems use a special-purpose DBMS. A common example is an email system that performs many of the functions of a general-purpose DBMS such as the insertion and deletion of messages composed of various items of data or associating messages with a particular email address; but these functions are limited to what is required to handle email and don't provide the user with all of the functionality that would be available using a general-purpose DBMS.
Application software can often access a database on behalf of end-users, without exposing the DBMS interface directly. Application programmers may use a wire protocol directly, or more likely through anapplication programming interface. Database designers and database administrators interact with the DBMS through dedicated interfaces to build and maintain the applications' databases, and thus need some more knowledge and understanding about how DBMSs operate and the DBMSs' external interfaces and tuning parameters.

History

Research

ExamplesEdit

One way to classify databases involves the type of their contents, for example:bibliographic, document-text, statistical, or multimedia objects. Another way is by their application area, for example: accounting, music compositions, movies, banking, manufacturing, or insurance. A third way is by some technical aspect, such as the database structure or interface type. This section lists a few of the adjectives used to characterize different kinds of databases.
  • An in-memory database is a database that primarily resides in main memory, but is typically backed-up by non-volatile computer data storage. Main memory databases are faster than disk databases, and so are often used where response time is critical, such as in telecommunications network equipment.[27]SAP HANA platform is a very hot topic for in-memory database. By May 2012, HANA was able to run on servers with 100TB main memory powered by IBM. The co founder of the company claimed that the system was big enough to run the 8 largest SAP customers.
  • An active database includes an event-driven architecture which can respond to conditions both inside and outside the database. Possible uses include security monitoring, alerting, statistics gathering and authorization. Many databases provide active database features in the form of database triggers.
  • A cloud database relies on cloud technology. Both the database and most of its DBMS reside remotely, "in the cloud", while its applications are both developed by programmers and later maintained and utilized by (application's) end-users through aweb browser and Open APIs.
  • Data warehouses archive data from operational databases and often from external sources such as market research firms. The warehouse becomes the central source of data for use by managers and other end-users who may not have access to operational data. For example, sales data might be aggregated to weekly totals and converted from internal product codes to useUPCs so that they can be compared withACNielsen data. Some basic and essential components of data warehousing include extracting, analyzing, and mining data, transforming, loading, and managing data so as to make them available for further use.
  • A deductive database combines logic programming with a relational database, for example by using the Datalog language.
  • A distributed database is one in which both the data and the DBMS span multiple computers.
  • A document-oriented database is designed for storing, retrieving, and managing document-oriented, or semi structured data, information. Document-oriented databases are one of the main categories of NoSQL databases.
  • An embedded database system is a DBMS which is tightly integrated with an application software that requires access to stored data in such a way that the DBMS is hidden from the application's end-users and requires little or no ongoing maintenance.[28]
  • End-user databases consist of data developed by individual end-users. Examples of these are collections of documents, spreadsheets, presentations, multimedia, and other files. Several products exist to support such databases. Some of them are much simpler than full-fledged DBMSs, with more elementary DBMS functionality.
  • A federated database system comprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated database management system (FDBMS), which transparently integrates multiple autonomous DBMSs, possibly of different types (in which case it would also be a heterogeneous database system), and provides them with an integrated conceptual view.
  • Sometimes the term multi-database is used as a synonym to federated database, though it may refer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group of databases that cooperate in a single application. In this case, typicallymiddleware is used for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-phase commit protocol, to allow distributed (global) transactions across the participating databases.
  • A graph database is a kind of NoSQL database that uses graph structures with nodes, edges, and properties to represent and store information. General graph databases that can store any graph are distinct from specialized graph databases such astriplestores and network databases.
  • An array DBMS is a kind of NoSQL DBMS that allows to model, store, and retrieve (usually large) multi-dimensional arrays such as satellite images and climate simulation output.
  • In a hypertext or hypermedia database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or a film, can be hyperlinked to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing online encyclopedias, where users can conveniently jump around the text. The World Wide Web is thus a large distributed hypertext database.
  • A knowledge base (abbreviated KB, kb or Δ[29][30]) is a special kind of database forknowledge management, providing the means for the computerized collection, organization, and retrieval of knowledge. Also a collection of data representing problems with their solutions and related experiences.
  • A mobile database can be carried on or synchronized from a mobile computing device.
  • Operational databases store detailed data about the operations of an organization. They typically process relatively high volumes of updates using transactions. Examples include customer databases that record contact, credit, and demographic information about a business' customers, personnel databases that hold information such as salary, benefits, skills data about employees,enterprise resource planning systems that record details about product components, parts inventory, and financial databases that keep track of the organization's money, accounting and financial dealings.
  • A parallel database seeks to improve performance through parallelization for tasks such as loading data, building indexes and evaluating queries.
The major parallel DBMS architectures which are induced by the underlyinghardware architecture are:
  • Shared memory architecture, where multiple processors share the main memory space, as well as other data storage.
  • Shared disk architecture, where each processing unit (typically consisting of multiple processors) has its own main memory, but all units share the other storage.
  • Shared nothing architecture, where each processing unit has its own main memory and other storage.
  • Probabilistic databases employ fuzzy logic to draw inferences from imprecise data.
  • Real-time databases process transactions fast enough for the result to come back and be acted on right away.
  • A spatial database can store the data with multidimensional features. The queries on such data include location-based queries, like "Where is the closest hotel in my area?".
  • A temporal database has built-in time aspects, for example a temporal data model and a temporal version of SQL. More specifically the temporal aspects usually include valid-time and transaction-time.
  • A terminology-oriented database builds upon an object-oriented database, often customized for a specific field.
  • An unstructured data database is intended to store in a manageable and protected way diverse objects that do not fit naturally and conveniently in common databases. It may include email messages, documents, journals, multimedia objects, etc. The name may be misleading since some objects can be highly structured. However, the entire possible object collection does not fit into a predefined structured framework. Most established DBMSs now support unstructured data in various ways, and new dedicated DBMSs are emerging.

Design and modelingEdit

Main article: Database design
Process of database design v2.png
The first task of a database designer is to produce a conceptual data model that reflects the structure of the information to be held in the database. A common approach to this is to develop an entity-relationship model, often with the aid of drawing tools. Another popular approach is the Unified Modeling Language. A successful data model will accurately reflect the possible state of the external world being modeled: for example, if people can have more than one phone number, it will allow this information to be captured. Designing a good conceptual data model requires a good understanding of the application domain; it typically involves asking deep questions about the things of interest to an organization, like "can a customer also be a supplier?", or "if a product is sold with two different forms of packaging, are those the same product or different products?", or "if a plane flies from New York to Dubai via Frankfurt, is that one flight or two (or maybe even three)?". The answers to these questions establish definitions of the terminology used for entities (customers, products, flights, flight segments) and their relationships and attributes.
Producing the conceptual data model sometimes involves input from business processes, or the analysis of workflow in the organization. This can help to establish what information is needed in the database, and what can be left out. For example, it can help when deciding whether the database needs to hold historic data as well as current data.
Having produced a conceptual data model that users are happy with, the next stage is to translate this into a schema that implements the relevant data structures within the database. This process is often called logical database design, and the output is a logical data model expressed in the form of a schema. Whereas the conceptual data model is (in theory at least) independent of the choice of database technology, the logical data model will be expressed in terms of a particular database model supported by the chosen DBMS. (The terms data model anddatabase model are often used interchangeably, but in this article we use data model for the design of a specific database, and database model for the modelling notation used to express that design.)
The most popular database model for general-purpose databases is the relational model, or more precisely, the relational model as represented by the SQL language. The process of creating a logical database design using this model uses a methodical approach known as normalization. The goal of normalization is to ensure that each elementary "fact" is only recorded in one place, so that insertions, updates, and deletions automatically maintain consistency.
The final stage of database design is to make the decisions that affect performance, scalability, recovery, security, and the like. This is often called physical database design. A key goal during this stage is data independence, meaning that the decisions made for performance optimization purposes should be invisible to end-users and applications. There are two types of data independence: Physical data independence and logical data independence. Physical design is driven mainly by performance requirements, and requires a good knowledge of the expected workload and access patterns, and a deep understanding of the features offered by the chosen DBMS.
Another aspect of physical database design is security. It involves both defining access control to database objects as well as defining security levels and methods for the data itself.

ModelsEdit

Main article: Database model
Collage of five types of database models
A database model is a type of data model that determines the logical structure of a database and fundamentally determines in which manner data can be stored, organized, and manipulated. The most popular example of a database model is the relational model (or the SQL approximation of relational), which uses a table-based format.
Common logical data models for databases include:
An object-relational database combines the two related structures.
Other models include:
Specialized models are optimized for particular types of data:

External, conceptual, and internal viewsEdit

Traditional view of data[31]
A database management system provides three views of the database data:
  • The external level defines how each group of end-users sees the organization of data in the database. A single database can have any number of views at the external level.
  • The conceptual level unifies the various external views into a compatible global view.[32] It provides the synthesis of all the external views. It is out of the scope of the various database end-users, and is rather of interest to database application developers and database administrators.
  • The internal level (or physical level) is the internal organization of data inside a DBMS. It is concerned with cost, performance, scalability and other operational matters. It deals with storage layout of the data, using storage structures such as indexes to enhance performance. Occasionally it stores data of individual views (materialized views), computed from generic data, if performance justification exists for such redundancy. It balances all the external views' performance requirements, possibly conflicting, in an attempt to optimize overall performance across all activities.
While there is typically only one conceptual (or logical) and physical (or internal) view of the data, there can be any number of different external views. This allows users to see database information in a more business-related way rather than from a technical, processing viewpoint. For example, a financial department of a company needs the payment details of all employees as part of the company's expenses, but does not need details about employees that are the interest of the human resources department. Thus different departments need different views of the company's database.
The three-level database architecture relates to the concept of data independence which was one of the major initial driving forces of the relational model. The idea is that changes made at a certain level do not affect the view at a higher level. For example, changes in the internal level do not affect application programs written using conceptual level interfaces, which reduces the impact of making physical changes to improve performance.
The conceptual view provides a level of indirection between internal and external. On one hand it provides a common view of the database, independent of different external view structures, and on the other hand it abstracts away details of how the data are stored or managed (internal level). In principle every level, and even every external view, can be presented by a different data model. In practice usually a given DBMS uses the same data model for both the external and the conceptual levels (e.g., relational model). The internal level, which is hidden inside the DBMS and depends on its implementation, requires a different level of detail and uses its own types of data structure types.
Separating the external, conceptual andinternal levels was a major feature of the relational database model implementations that dominate 21st century databases.[32]

LanguagesEdit

Database languages are special-purpose languages, which do one or more of the following:
Database languages are specific to a particular data model.Notable examples include:
A database language may also incorporate features like:
  • DBMS-specific Configuration and storage engine management
  • Computations to modify query results, like counting, summing, averaging, sorting, grouping, and cross-referencing
  • Constraint enforcement (e.g. in an automotive database, only allowing one engine type per car)
  • Application programming interface version of the query language, for programmer convenience

Performance, security, and availabilityEdit

Because of the critical importance of database technology to the smooth running of an enterprise, database systems include complex mechanisms to deliver the required performance, security, and availability, and allow database administrators to control the use of these features.

StorageEdit

Main articles: Computer data storage and Database engine
Database storage is the container of the physical materialization of a database. It comprises the internal (physical) level in the database architecture. It also contains all the information needed (e.g., metadata, "data about the data", and internal data structures) to reconstruct the conceptual level andexternal level from the internal level when needed. Putting data into permanent storage is generally the responsibility of the database engine a.k.a. "storage engine". Though typically accessed by a DBMS through the underlying operating system (and often utilizing the operating systems' file systemsas intermediates for storage layout), storage properties and configuration setting are extremely important for the efficient operation of the DBMS, and thus are closely maintained by database administrators. A DBMS, while in operation, always has its database residing in several types of storage (e.g., memory and external storage). The database data and the additional needed information, possibly in very large amounts, are coded into bits. Data typically reside in the storage in structures that look completely different from the way the data look in the conceptual and external levels, but in ways that attempt to optimize (the best possible) these levels' reconstruction when needed by users and programs, as well as for computing additional types of needed information from the data (e.g., when querying the database).
Some DBMSs support specifying whichcharacter encoding was used to store data, so multiple encodings can be used in the same database.
Various low-level database storage structuresare used by the storage engine to serialize the data model so it can be written to the medium of choice. Techniques such as indexing may be used to improve performance. Conventional storage is row-oriented, but there are also column-oriented and correlation databases.

Materialized viewsEdit

Main article: Materialized view
Often storage redundancy is employed to increase performance. A common example is storing materialized views, which consist of frequently needed external views or query results. Storing such views saves the expensive computing of them each time they are needed. The downsides of materialized views are the overhead incurred when updating them to keep them synchronized with their original updated database data, and the cost of storage redundancy.

ReplicationEdit

Main article: Database replication
Occasionally a database employs storage redundancy by database objects replication (with one or more copies) to increase data availability (both to improve performance of simultaneous multiple end-user accesses to a same database object, and to provide resiliency in a case of partial failure of a distributed database). Updates of a replicated object need to be synchronized across the object copies. In many cases, the entire database is replicated.

SecurityEdit

Main article: Database security
Database security deals with all various aspects of protecting the database content, its owners, and its users. It ranges from protection from intentional unauthorized database uses to unintentional database accesses by unauthorized entities (e.g., a person or a computer program).
Database access control deals with controlling who (a person or a certain computer program) is allowed to access what information in the database. The information may comprise specific database objects (e.g., record types, specific records, data structures), certain computations over certain objects (e.g., query types, or specific queries), or utilizing specific access paths to the former (e.g., using specific indexes or other data structures to access information). Database access controls are set by special authorized (by the database owner) personnel that uses dedicated protected security DBMS interfaces.
This may be managed directly on an individual basis, or by the assignment of individuals andprivileges to groups, or (in the most elaborate models) through the assignment of individuals and groups to roles which are then granted entitlements. Data security prevents unauthorized users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of it called "subschemas". For example, an employee database can contain all the data about an individual employee, but one group of users may be authorized to view only payroll data, while others are allowed access to only work history and medical data. If the DBMS provides a way to interactively enter and update the database, as well as interrogate it, this capability allows for managing personal databases.
Data security in general deals with protecting specific chunks of data, both physically (i.e., from corruption, or destruction, or removal; e.g., see physical security), or the interpretation of them, or parts of them to meaningful information (e.g., by looking at the strings of bits that they comprise, concluding specific valid credit-card numbers; e.g., seedata encryption).
Change and access logging records who accessed which attributes, what was changed, and when it was changed. Logging services allow for a forensic database auditlater by keeping a record of access occurrences and changes. Sometimes application-level code is used to record changes rather than leaving this to the database. Monitoring can be set up to attempt to detect security breaches.

Transactions and concurrencyEdit

Further information: Concurrency control
Database transactions can be used to introduce some level of fault tolerance anddata integrity after recovery from a crash. A database transaction is a unit of work, typically encapsulating a number of operations over a database (e.g., reading a database object, writing, acquiring lock, etc.), an abstraction supported in database and also other systems. Each transaction has well defined boundaries in terms of which program/code executions are included in that transaction (determined by the transaction's programmer via special transaction commands).
The acronym ACID describes some ideal properties of a database transaction:Atomicity, Consistency, Isolation, andDurability.

MigrationEdit

See also: Data migration § Database migration
A database built with one DBMS is not portable to another DBMS (i.e., the other DBMS cannot run it). However, in some situations, it is desirable to move, migrate a database from one DBMS to another. The reasons are primarily economical (different DBMSs may have different total costs of ownership or TCOs), functional, and operational (different DBMSs may have different capabilities). The migration involves the database's transformation from one DBMS type to another. The transformation should maintain (if possible) the database related application (i.e., all related application programs) intact. Thus, the database's conceptual and external architectural levels should be maintained in the transformation. It may be desired that also some aspects of the architecture internal level are maintained. A complex or large database migration may be a complicated and costly (one-time) project by itself, which should be factored into the decision to migrate. This in spite of the fact that tools may exist to help migration between specific DBMSs. Typically, a DBMS vendor provides tools to help importing databases from other popular DBMSs.

Building, maintaining, and tuningEdit

Main article: Database tuning
After designing a database for an application, the next stage is building the database. Typically, an appropriate general-purpose DBMS can be selected to be utilized for this purpose. A DBMS provides the needed user interfaces to be utilized by database administrators to define the needed application's data structures within the DBMS's respective data model. Other user interfaces are used to select needed DBMS parameters (like security related, storage allocation parameters, etc.).
When the database is ready (all its data structures and other needed components are defined), it is typically populated with initial application's data (database initialization, which is typically a distinct project; in many cases using specialized DBMS interfaces that support bulk insertion) before making it operational. In some cases, the database becomes operational while empty of application data, and data are accumulated during its operation.
After the database is created, initialised and populated it needs to be maintained. Various database parameters may need changing and the database may need to be tuned (tuning) for better performance; application's data structures may be changed or added, new related application programs may be written to add to the application's functionality, etc.

Backup and restoreEdit

Main article: Backup
Sometimes it is desired to bring a database back to a previous state (for many reasons, e.g., cases when the database is found corrupted due to a software error, or if it has been updated with erroneous data). To achieve this, a backup operation is done occasionally or continuously, where each desired database state (i.e., the values of its data and their embedding in database's data structures) is kept within dedicated backup files (many techniques exist to do this effectively). When this state is needed, i.e., when it is decided by a database administrator to bring the database back to this state (e.g., by specifying this state by a desired point in time when the database was in this state), these files are utilized to restorethat state.

Static analysisEdit

Static analysis techniques for software verification can be applied also in the scenario of query languages. In particular, the *Abstract interpretation framework has been extended to the field of query languages for relational databases as a way to support sound approximation techniques.[36] The semantics of query languages can be tuned according to suitable abstractions of the concrete domain of data. The abstraction of relational database system has many interesting applications, in particular, for security purposes, such as fine grained access control, watermarking, etc.

OtherEdit

Other DBMS features might include:
  • Database logs
  • Graphics component for producing graphs and charts, especially in a data warehouse system
  • Query optimizer – Performs query optimization on every query to choose an efficient query plan (a partial order (tree) of operations) to be executed to compute the query result. May be specific to a particular storage engine.
  • Tools or hooks for database design, application programming, application program maintenance, database performance analysis and monitoring, database configuration monitoring, DBMS hardware configuration (a DBMS and related database may span computers, networks, and storage units) and related database mapping (especially for a distributed DBMS), storage allocation and database layout monitoring, storage migration, etc.
  • Increasingly, there are calls for a single system that incorporates all of these core functionalities into the same build, test, and deployment framework for database management and source control. Borrowing from other developments in the software industry, some market such offerings as "DevOps for database".[37]

See also

Notes

References

SourcesEdit

  • Beynon–Davies, Paul (2003). Database Systems (3rd ed.). Palgrave Macmillan.ISBN 978-1403916013.
  • Chapple, Mike (2005). "SQL Fundamentals". Databases. About.com.Archived from the original on 22 February 2009. Retrieved 28 January 2009.
  • Chong, Raul F.; Wang, Xiaomei; Dang, Michael; Snow, Dwaine R. (2007)."Introduction to DB2". Understanding DB2: Learning Visually with Examples (2nd ed.).ISBN 978-0131580183. Retrieved 17 March2013.
  • Nelson, Anne Fulcher; Nelson, William Harris Morehead (2001). Building Electronic Commerce: With Web Database Constructions. Prentice Hall. ISBN 978-0201741308.
  • Tsitchizris, Dionysios C.; Lochovsky, Fred H. (1982). Data Models. Prentice–Hall.ISBN 978-0131964280.
  • Ullman, Jeffrey; Widom, Jennifer (1997).A First Course in Database Systems. Prentice–Hall. ISBN 0138613370.
  • Wagner, Michael (2010), SQL/XML:2006 – Evaluierung der Standardkonformität ausgewählter Datenbanksysteme, Diplomica Verlag, ISBN 978-3836696098

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