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 users. Typical examples of DBMS use include accounting, human resources and customer support systems. Originally found only in large companies 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 multitasking kernel with built-in networking 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 normalized, data. Examples include Oracle Database, DB2, Microsoft SQL Server, MySQL and PostgreSQL. Nowadays a small number of DBMSs are used by the great majority of database applications to manage practically all the world's databases.

A database application is computer software written to manage the data of a particular application or problem set. This software usually employs a DBMS for the generalised data management issues. Examples include Microsoft Money, Oracle Human Resources, Sage Payroll, and the most of the countless other database applications written either in-house or by the thousands of software houses around the world.

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 price of flexibility.

Navigational DBMS

As computers grew in capability this tradeoff became increasingly unnecessary, as a number of general-purpose database systems emerged, and by the mid-1960s there were a number of such systems in commercial use. Interest in a standard started to grow, and Charles Bachman, author of one such product, IDS, 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 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.

IBM also had their own DBMS system in 1968, known as IMS. IMS was a development of software written for the Apollo program 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 database. IDS and IDMS (both CODASYL databases) as well as CINCOMs TOTAL database are classified as network databases.

Relational DBMS

Edgar Codd worked at IBM 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 and 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" 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.

In the relational model, related records are linked together with a "key".

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.

IBM started working on a prototype system based on Codd's concepts as System R in the early 1970s. 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 products version of System R, known as SQL/DS, and, later, Database 2 (DB2).

Codd's paper was also 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. Starting in 1973, INGRES delivered its first test products in 1974, and was 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.

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. 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 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, and is used 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).

After that Stonebraker went on to found Sleepycat Software, which produces a very widely used embedded database called BerkeleyDB.

Even in Sweden Codd's paper was read, and 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.

Multidimensional DBMS

Relational (or near-relational) DBMS implementations (Oracle, Sybase, et al) soon dominated the database market. But the query performance in fully normalized relational databases can be quite poor. For instance, to find the address of the user named Bob, these implementations may look up Bob in the USER table, find his "primary key" (the login name), and then search the ADDRESS table for that key. Although this appears to be a single operation to the user, in most implementations it requires a complex and time consuming search through the tables.

In response database programmers have turned to denormalization to help improve performance, but such violations of database normalization carries with it a heavy cost (namely the cost of data redundancies and the extra data-checking logic to ensure the database remains consistent). But a more serious cost is that relational database management systems are unable to store many to one relationships without normalisation: As a consequence Oracle, Sybase, MS SQL Server etc are not well suited to the storage of denormalised data: Other database management systems such as Pick have been used instead.

Multidimensional DBMSs ignore the logical/physical independence tenet of the relational model and instead exposes pointers to the programmer. Instead of finding Bob's address by looking up the "key" in the address table, the multidimensional DBMS store a pointer to the data in question. In fact, if the data is "owned" by the original record (that is, no other records in USER point to it), it can be stored in the same physical location, thereby increasing the speed at which it can be accessed.

This sort of physical data optimization can (and should) be done in current pseudo-relational systems but still allowing for logical data independence (the programmer would still see the “key” value but internally it would be stored as a pointer).

Due to poor timing (and generally poor implementations) as a general solution the multidimensional system never became popular, although certain ideas have been picked up in Object DBMS.

Object-oriented DBMS

Multidimensional DBMS did have one lasting impact on the market: they led directly to the development of the 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 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, storage and retrieval of data (fields, records and files) in a database. It also controls the security and integrity of the database. 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.

Data security prevents unauthorised users from viewing or updating the database. Using passwords, users are allowed access to the entire database or subsets of the database, 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.

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.

Database query languages and report writers allow users to interactively interrogate the database and analyse its 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 business information system is made up of subjects (customers, employees, vendors, etc.) and activities (orders, payments, purchases, etc.). Database design is the process of deciding how to organize these data into record types and how the record types will relate to each other. The DBMS should mirror the organization's data structure and process transactions efficiently.

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.

The three most common organizations are the hierarchical, network and relational 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 relational model, usually used with the SQL query language. Many DBMSs also support the Open Database Connectivity API that supports a standard way for programmers to access the DBMS.

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 RAID 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.