Database management system

A database management system (DBMS) is a computer program (or more typically, a suite of them) designed to manage a Database (a large set of structured Data), and run operations on the data requested by numerous consumers. Typical examples of DBMS use include accounting, human resources and customer support systems. Originally found only in large organizations with the computer hardware needed to support large data sets, DBMSs have more recently emerged as a fairly standard part of any company back office.

DBMS s are found at the heart of most database applications. Sometimes DBMSs are built around a private computer multitasking Kernel (computers) with built-in Computer network support although nowadays these functions are left to the operating system.

==Terminology==

A database management system (DBMS) is a system, usually automated and computerized, for the management of any collection of compatible, and ideally Database normalization, data. Examples include DB2, Microsoft SQL Server, MySQL, Oracle database, and PostgreSQL.

A database application is computer software written to manage the data of a particular application software or problem set. This software usually employs a DBMS for the generalised data management issues. Examples include Microsoft Access, Oracle Human Resources, Sage Payroll, and many other database applications.

A Database or dataset is a particular collection of related and structured data. Examples include Social Security numbers, voter rolls, lists of houses for sale, and accounting records. There are many millions of databases. Each database application might be implemented many times, each implementation managing its own particular database or databases.

=History=

Databases have been in use since the earliest days of electronic computing, but the vast majority of these were custom programs written to access custom databases. Unlike modern systems which can be applied to widely different databases and needs, these systems were tightly linked to the database in order to gain speed at the expense of flexibility.

==Navigational DBMS==

As computers grew in capability this tradeoff became increasingly unnecessary and a number of general-purpose database systems emerged; by the mid-1960s there were a number of such systems in commercial use. Interest in a standard began to grow, and Charles Bachman, author of one such product, Integrated Data Store, founded the Database Task Group within CODASYL, the group responsible for the creation and standardization of COBOL. In 1971 they delivered their standard, which generally became known as the Codasyl approach, and soon there were a number of commercial products based on it available..

The Codasyl approach was based on the manual navigation of a linked dataset which was formed into a large network. When the database was first opened, the program was handed back a link to the first database record in the database, which also contained Pointers to other pieces of data. To find any particular record the programmer had to step through these pointers one at a time until the required record was returned. Simple queries like find all the people in Sweden required the program to walk the entire data set and collect the matching results. There was, essentially, no concept of find or search . This might sound like a serious limitation today, but in an era when the data was most often stored on magnetic tape such operations were too expensive to contemplate anyway.

International Business Machines also had their own DBMS system in 1968, known as IMS. Information Management System was a development of software written for the Project Apollo on the System/360. IMS was generally similar in concept to Codasyl, but used a strict hierarchy for its model of data navigation instead of Codasyl s network model.

Both concepts later became known as navigational databases due to the way data was accessed, and Bachman s 1973 Turing Award award presentation was The Programmer as Navigator . IMS is classified as a Hierarchical model. IDS and IDMS (both CODASYL databases) as well as Cincoms TOTAL (database) database are classified as network model.

==Relational DBMS==

Edgar Codd worked at International Business Machines in San Jose, California, in one of their offshoot offices that was primarily involved in the development of hard disk systems. He was unhappy with the navigational model of the Codasyl approach, notably the lack of a search facility which was becoming increasingly useful when the database was stored on disk instead of tape. In 1970 he wrote a number of papers that outlined a new approach to database construction that eventually culminated in the groundbreaking A Relational Model of Data for Large Shared Data Banks .

In this paper he described a new system for storing and working with large databases. Instead of records being stored in some sort of linked list of free-form records as in Codasyl, Codd s idea was to use a Table (database) of fixed-length records. A linked-list system would be very inefficient when storing sparse databases where some of the data for any one record could be left empty. The relational model solved this by splitting the data into a series of tables, with optional elements being moved out of the main table to where they would take up room only if needed.

For instance, a common use of a database system is to track information about users, their name, login information, various addresses and phone numbers. In the navigational approach all of these data would be placed in a single record, and unused items would simply not be placed in the database. In the relational approach, the data would be split into a user table, an address table and a phone number table (for instance). Records would be created in these optional tables only if the address or phone numbers were actually provided.

Linking the information back together is the key to this system. In the relational model some bit of information was used as a key , uniquely defining a particular record. When information was being collected about a user, information stored in the optional (or related ) tables would be found by searching for this key. For instance, if the login name of a user is unique, addresses and phone numbers for that user would be recorded with the login name as its key. This re-linking of related data back into a single collection is something that traditional computer languages are not designed for.

Just as the navigational approach would require programs to loop in order to collect records, the relational approach would require loops to collect information about any one record. Codd s solution to the necessary looping was a set-oriented language, a suggestion that would later spawn the ubiquitous SQL. Using a branch of mathematics known as tuple calculus , he demonstrated that such a system could support all the operations of normal databases (inserting, updating etc.) as well as providing a simple system for finding and returning sets of data in a single operation.

Codd s paper was picked up by two people at Berkeley, Eugene Wong and Michael Stonebraker. They started a project known as Ingres using funding that had already been allocated for a geographical database project, using student programmers to produce code. Beginning in 1973, INGRES delivered its first test products which were generally ready for widespread use in 1979. During this time a number of people had moved through the group — perhaps as many as 30 people worked on the project, about five at a time. INGRES was similar to System R in a number of ways, including the use of a language for data access, known as QUEL — QUEL was in fact relational, having been based on Codd s own Alpha language, but has since been corrupted to follow SQL, thus violating much the same concepts of the relational model as SQL itself.

IBM itself did only one test implementation of the relational model, . All other DBMS implementations usually called relational are actually SQL DBMSs.

==SQL DBMS==

IBM started working on a prototype system loosely based on Codd s concepts as System R in the early 1970s — unfortunately System R was conceived as a way of proving Codd s ideas unimplementable, and thus the project was delivered to a group of programmers who weren t under Codd s supervision, never understood his ideas fully and ended up violating several fundamentals of the relational model. The first quickie version was ready in 1974/5, and work then started on multi-table systems in which the data could be broken down so that all of the data for a record (much of which is often optional) didn t have to be stored in a single large chunk . Subsequent multi-user versions were tested by customers in 1978 and 79, by which time a standardized computer language, SQL, had been added. Codd s ideas were establishing themselves as both workable and superior to Codasyl, pushing IBM to develop a true production version of System R, known as SQL/DS, and, later, Database 2 (DB2).

Many of the people involved with INGRES became convinced of the future commercial success of such systems, and formed their own companies to commercialize the work but with an SQL interface. Sybase, Informix, NonStop SQL and eventually Ingres itself were all being sold as offshoots to the original INGRES product in the 1980s. Even Microsoft SQL Server is actually a re-built version of Sybase, and thus, INGRES. Only Larry Ellison s Oracle Corporation started from a different chain, based on IBM s papers on System R by beating them to market when the first version was released in 1978.

Stonebraker went on to apply the lessons from INGRES to develop a new database, Postgres, now known as PostgreSQL. PostgreSQL is now one of the most widely used databases in the world, primarily for global mission critical applications (the .org and .info domain name registries use it as their primary data store, as do many large companies and financial institutions).

In Sweden Codd s paper was also read, Mimer SQL was developed from the mid-70s at Uppsala University, and in 1984 this project was consolidated into an independent enterprise. In the early 1980s Mimer introduced transaction handling for high robustness in applications, an idea that was subsequently implemented on most other DBMSs.

==Object-oriented DBMS==

Multidimensional DBMS did have one lasting impact on the market: they led directly to the development of object database systems. Based on the same general structure and concepts as the multidimensional systems, these new systems allowed the user to store objects directly in the database. That is, the programming constructs being used in the object oriented (OO) programming world could be used directly in the database, instead of first being converted to some other format.

This could happen because of the multidimensional system s concepts of ownership. In an OO program a particular object will typically contain others; for example, the object representing Bob may contain a reference to a separate object referring to Bob s home address. Adding support for various OO languages and polymorphism (computer science) re-created the multidimensional systems as object databases, which continue to serve a niche today.

=Description=

A DBMS can be an extremely complex set of software programs that controls the organization, Computer storage and Data retrieval of data (fields, records and files) in a Database. The basic functionalities that a DBMS must provide are: # A Data modeling Formal language to define the schema of each Database hosted in the DBMS, according to the DBMS data model. #*The three most common organizations are the hierarchical model, network model and relational model models. A database management system may provide one, two or all three methods. Inverted lists and other methods are also used. The most suitable structure depends on the application and on the transaction rate and the number of inquiries that will be made.The dominant model in use today is the ad hoc one embedded in SQL, a corruption of the relational model by violating several of its fundamental principles. Many DBMSs also support the Open Database Connectivity API that supports a standard way for programmers to access the DBMS. # Data structures optimized to deal with big amounts of data recorded to a Digital permanence data storage device, which are very slow Computer storage to the primary storage (volatile main memory). # A database query language and report writer to allow users to interactively interrogate the database, analyse its data and update it according to the Privilege (Computing) on data. #*It also controls the security of the database. #*Data security prevents unauthorised users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of it called subschemas (pronounced sub-skeema ). 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. However, it may not leave an audit trail of actions or provide the kinds of controls necessary in a multi-user organisation. These controls are only available when a set of application programs are customised for each data entry and updating function. # A Database transaction mechanism, that ideally would guarantee the ACID properties, in order to ensure data integrity despite of Concurrency (computer science) (concurrency control) and faults (fault tolerance). #*It also controls the integrity of the database. #*The DBMS can maintain the integrity of the database by not allowing more than one user to update the same record at the same time. The DBMS can keep duplicate records out of the database; for example, no two customers with the same customer numbers (key fields) can be entered into the database. See ACID properties for more information (Reduncdancy avoidance).

The DBMS accepts requests for data from the application program and instructs the operating system to transfer the appropriate data.

When a DBMS is used, information systems can be changed much more easily as the organization s information requirements change. New categories of data can be added to the database without disruption to the existing system.

Organizations may use one kind of DBMS for daily transaction processing and then move the detail onto another computer that uses another DBMS better suited for random inquiries and analysis. Overall systems design decisions are performed by data administrators and systems analysts. Detailed database design is performed by database administrators.

Database servers are specially designed computers that hold the actual databases and run only the DBMS and related software. Database servers are usually multiprocessor computers, with redundant array of independent disks disk arrays used for stable storage. Connected to one or more servers via a high-speed channel, hardware database accelerators are also used in large volume transaction processing environments.

=See also=

*Data warehouse *Directory service *Distributed Database Management System *Navigational database management system *Hierarchical database management system *Network database management system *Object database (OODBMS) *Relational database management system (RDBMS) *Object-relational database management system (ORDBMS)