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A database is an integrated collection of logically related records or files which consolidates records into a common pool of data records that provides data for many applications. A database is a collection of information that is organized so that it can easily be accessed, managed, and updated.

In one view, databases can be classified according to types of content: bibliographic, full-text, numeric, and images.

The data in a database is organized according to a database model. The model that is most commonly used today is the relational model. Other models such as the hierarchical model and the network model use a more explicit representation of relationships.

Database topics


Depending on the intended use, there are a number of database architectures in use. Many databases use a combination of strategies. On-line Transaction Processing systems (OLTP) often use a row-oriented datastore architecture, while data-warehouse and other retrieval-focused applications like Google's BigTable, or bibliographic database (library catalogue) systems may use a Column-oriented DBMS architecture.

Document-Oriented, XML, knowledgebases, as well as frame databases and RDF-stores (aka triple-stores), may also use a combination of these architectures in their implementation.

Finally, it should be noted that not all databases have or need a database schema (so called schema-less databases).

Over many years the database industry has been dominated by General Purpose database systems, which offer a wide range of functions that are applicable to many, if not most circumstances in modern data processing. These have been enhanced with extensible datatypes, pioneered in the PostgreSQL project, to allow a very wide range of applications to be developed.

There are also other types of database which cannot be classified as relational databases.

Database management systems

A database management system (DBMS) is software that organizes the storage of data. It controls the creation, maintenance, and the use of the database tables of an organization and its end users. It allows organizations to place control of organizationwide database development in the hands of Database Administrators (DBAs) and other specialist. In large systems, a DBMS allows users and other software to store and retrieve data in a structured way.

Database management systems are categorized according to the database model that they support, such as the network model or relational model. The model tends to determine the query languages that are available to access the database. One commonly used query language is SQL, although SQL syntax and function can vary from one DBMS to another. A great deal of the internal engineering of a DBMS, is independent of the data model, and is concerned with managing factors such as performance, concurrency, integrity, and recovery from hardware failures. In these areas there are large differences between products.

A relational database management system (RDBMS) implements the features of the relational model. In this context, Date's "Information Principle" states: "the entire information content of the database is represented in one and only one way. Namely as explicit values in column positions (attributes) and rows in relations (tuples). Therefore, there are no explicit pointers between related tables."

Five components of DBMS

According to the wikibooks open-content textbooks, "Design of Main Memory Database System/Overview of DBMS" Most of the DBMS present today are relational DBMS. RDBMS has five main components

  • Interface drivers - A user or application program shall initiate either schema modification or content modification. These drivers are built on top of SQL. They provide methods to prepare statements, execute statements, fetch results, etc. Examples: DDL, DCL, DML, ODBC, and JDBC. Some vendors provide language specific proprietary interfaces. For example MySQL provides drivers for PHP, Python, etc.
  • SQL Engine - This component is responsible for interpreting and executing the SQL query. It comprises of three major components
  • Transaction Engine - Transactions are sequence of operations that read or write database elements, which are grouped together.
  • Relational Engine - Relational objects such as Table, Index, and Referential integrity constraints are implemented in this component.
  • Storage Engine - This component is responsible to store and retrieve data records. It also provides mechanism to store meta data information and control information such as undo logs, redo logs, lock tables, etc.

Primary tasks of DBMS packages

  • Database Development. It is used to define and organize the content, relationships, and structure of the data needed to build a database.
  • Database Interrogation. It can access the data in a database for information retrieval and report generation. End users can selectively retrieve and display information and produce printed reports and documents.
  • Database Maintenance. It is used to add, delete, update, correct, and protect the data in a database.
  • Application Development. It is used to develop prototypes of data entry screens, queries, forms, reports, tables, and labels for a prototyped application. Or use 4GL or 4th Generation Language or application generator to develop program codes.

Types of databases

Operational database

These databases store detailed data needed to support the operations of the entire organization. They are also called subject-area databases (SADB), transaction databases, and production databases. These are all examples:

  • Customer databases
  • Personal databases
  • Inventory databases

Analytical database

These databases stores data and information extracted from selected operational and external databases. They consist of summarized data and information most needed by an organizations manager and other end user. They may also be called multidimensional database, Management database, and Information database.

Data warehouse

A data warehouse stores data from current and previous years that has been extracted from the various operational databases of an organization. It is the central source of data that has been screened, edited, standardized and integrated so that it can be used by managers and other end user professionals throughout an organization

Distributed database

These are databases of local work groups and departments at regional offices, branch offices, manufacturing plants and other work sites. These databases can include segments of both common operational and common user databases, as well as data generated and used only at a user’s own site.

End-user database

These databases consist of a variety of data files developed by end-users at their workstations. Examples of these are collection of documents in spreadsheets, word processing and even downloaded files.

External database

These databases where access to external, privately owned online databases or data banks is available for a fee to end users and organizations from commercial services. Access to a wealth of information from external database is available for a fee from commercial online services and with or without charge from many sources in the internet.

Hypermedia databases on the Web

These are set of interconnected multimedia pages at a web-site. It consists of home page and other hyperlinked pages of multimedia or mixed media such as text, graphic, photographic images, video clips, audio etc.

Navigational database

Navigational databases are characterized by the fact that objects in it are found primarily by following references from other objects. Traditionally navigational interfaces are procedural, though one could characterize some modern systems like XPath as being simultaneously navigational and declarative.

In-memory databases

In-memory databases are database management systems that primarily rely on main memory for computer data storage. It is contrasted with database management systems which employ a disk storage mechanism. Main memory databases are faster than disk-optimized databases since the internal optimization algorithms are simpler and execute fewer CPU instructions. Accessing data in memory provides faster and more predictable performance than disk. In applications where response time is critical, such as telecommunications network equipment that operates 9-1-1 emergency systems, main memory databases are often used.

Document-oriented databases

Document-oriented databases are computer programs designed for document-oriented applications. These systems may be implemented as a layer above a relational database or an object database. As opposed to relational databases, document-based databases do not store data in tables with uniform sized fields for each record. Instead, each record is stored as a document that has certain characteristics. Any number of fields of any length can be added to a document. Fields can also contain multiple pieces of data.

Real-time databases

A real-time database is a processing system designed to handle workloads whose state is constantly changing. This differs from traditional databases containing persistent data, mostly unaffected by time. For example, a stock market changes very rapidly and is dynamic. Real-time processing means that a transaction is processed fast enough for the result to come back and be acted on right away. Real-time databases are useful for accounting, banking, law, medical records, multi-media, process control, reservation systems, and scientific data analysis. As computers increase in power and can store more data, they are integrating themselves into our society and are employed in many applications.

Database models

Post-relational database models

Products offering a more general data model than the relational model are sometimes classified as post-relational. The data model in such products incorporates relations but is not constrained by the Information Principle[clarification needed], which requires that all information is represented by data values in relations.[original research?]

Some of these extensions to the relational model actually integrate concepts from technologies that pre-date the relational model. For example, they allow representation of a directed graph with trees on the nodes.

Some products implementing such models have been built by extending relational database systems with non-relational features. Others, however, have arrived in much the same place by adding relational features to pre-relational systems. Paradoxically, this allows products that are historically pre-relational, such as PICK and MUMPS, to make a plausible claim to be post-relational in their current architecture.

Object database models

In recent years, the object-oriented paradigm has been applied to database technology, creating a various kinds of new programming model known as object databases. These databases attempt to bring the database world and the application programming world closer together, in particular by ensuring that the database uses the same type system as the application program. This aims to avoid the overhead (sometimes referred to as the impedance mismatch) of converting information between its representation in the database (for example as rows in tables) and its representation in the application program (typically as objects). At the same time, object databases attempt to introduce the key ideas of object programming, such as encapsulation and polymorphism, into the world of databases.

A variety of these ways have been tried for storing objects in a database. Some products have approached the problem from the application programming end, by making the objects manipulated by the program persistent. This also typically requires the addition of some kind of query language, since conventional programming languages do not have the ability to find objects based on their information content. Others have attacked the problem from the database end, by defining an object-oriented data model for the database, and defining a database programming language that allows full programming capabilities as well as traditional query facilities.

Database storage structures

Relational database tables/indexes are typically stored in memory or on hard disk in one of many forms, ordered/unordered flat files, ISAM, heaps, hash buckets or B+ trees. These have various advantages and disadvantages discussed further in the main article on this topic. The most commonly used are B+ trees and ISAM.

Object databases use a range of storage mechanisms. Some use virtual memory mapped files to make the native language (C++, Java etc.) objects persistent. This can be highly efficient but it can make multi-language access more difficult. Others break the objects down into fixed and varying length components that are then clustered tightly together in fixed sized blocks on disk and reassembled into the appropriate format either for the client or in the client address space. Another popular technique is to store the objects in tuples, much like a relational database, which the database server then reassembles for the client.

Other important design choices relate to the clustering of data by category (such as grouping data by month, or location), creating pre-computed views known as materialized views, partitioning data by range or hash. Memory management and storage topology can be important design choices for database designers as well. Just as normalization is used to reduce storage requirements and improve the extensibility of the database, conversely denormalization is often used to reduce join complexity and reduce execution time for queries.[1]


All of these databases can take advantage of indexing to increase their speed. This technology has advanced tremendously since its early uses in the 1960s and 1970s. The most common kind of index is a sorted list of the contents of some particular table column, with pointers to the row associated with the value. An index allows a set of table rows matching some criterion to be located quickly. Typically, indexes are also stored in the various forms of data-structure mentioned above (such as B-trees, hashes, and linked lists). Usually, a specific technique is chosen by the database designer to increase efficiency in the particular case of the type of index required.

Most relational DBMS's and some object DBMSs have the advantage that indexes can be created or dropped without changing existing applications making use of it. The database chooses between many different strategies based on which one it estimates will run the fastest. In other words, indexes are transparent to the application or end-user querying the database; while they affect performance, any SQL command will run with or without index to compute the result of an SQL statement. The RDBMS will produce a plan of how to execute the query, which is generated by analyzing the run times of the different algorithms and selecting the quickest. Some of the key algorithms that deal with joins are nested loop join, sort-merge join and hash join. Which of these is chosen depends on whether an index exists, what type it is, and its cardinality.

An index speeds up access to data, but it has disadvantages as well. First, every index increases the amount of storage on the hard drive necessary for the database file, and second, the index must be updated each time the data are altered, and this costs time. (Thus an index saves time in the reading of data, but it costs time in entering and altering data. It thus depends on the use to which the data are to be put whether an index is on the whole a net plus or minus in the quest for efficiency.)

A special case of an index is a primary index, or primary key, which is distinguished in that the primary index must ensure a unique reference to a record. Often, for this purpose one simply uses a running index number (ID number). Primary indexes play a significant role in relational databases, and they can speed up access to data considerably.

Transactions and concurrency

In addition to their data model, most practical databases ("transactional databases") attempt to enforce a database transaction. Ideally, the database software should enforce the ACID rules, summarized here:

  • Atomicity: Either all the tasks in a transaction must be done, or none of them. The transaction must be completed, or else it must be undone (rolled back).
  • Consistency: Every transaction must preserve the integrity constraints — the declared consistency rules — of the database. It cannot place the data in a contradictory state.
  • Isolation: Two simultaneous transactions cannot interfere with one another. Intermediate results within a transaction are not visible to other transactions.
  • Durability: Completed transactions cannot be aborted later or their results discarded. They must persist through (for instance) restarts of the DBMS after crashes

In practice, many DBMSs allow most of these rules to be selectively relaxed for better performance.

Concurrency control is a method used to ensure that transactions are executed in a safe manner and follow the ACID rules. The DBMS must be able to ensure that only serializable, recoverable schedules are allowed, and that no actions of committed transactions are lost while undoing aborted transactions.


Replication of databases is closely related to transactions. If a database can log its individual actions, it is possible to create a duplicate of the data in real time. The duplicate can be used to improve performance or availability of the whole database system. Common replication concepts include:

  • Master/Slave Replication: All write requests are performed on the master and then replicated to the slaves
  • Quorum: The result of Read and Write requests are calculated by querying a "majority" of replicas.
  • Multimaster: Two or more replicas sync each other via a transaction identifier.

Parallel synchronous replication of databases enables transactions to be replicated on multiple servers simultaneously, which provides a method for backup and security as well as data availability.


Database security denotes the system, processes, and procedures that protect a database from unintended activity.

Security is usually enforced through access control, auditing, and encryption.

  • Access control ensures and restricts who can connect and what can be done to the database.
  • Auditing logs what action or change has been performed, when and by whom.
  • Encryption: Since security has become a major issue in recent years, many commercial database vendors provide built-in encryption mechanisms. Data is encoded natively into the tables and deciphered "on the fly" when a query comes in. Connections can also be secured and encrypted if required using DSA, MD5, SSL or legacy encryption standard.

Enforcing security is one of the major tasks of the DBA.

In the United Kingdom, legislation protecting the public from unauthorized disclosure of personal information held on databases falls under the Office of the Information Commissioner. United Kingdom based organizations holding personal data in electronic format (databases for example) are required to register with the Data Commissioner.[2]


Locking is how the database handles multiple concurrent operations. This is how concurrency and some form of basic integrity is managed within the database system. Such locks can be applied on a row level, or on other levels like page (a basic data block), extent (multiple array of pages) or even an entire table. This helps maintain the integrity of the data by ensuring that only one process at a time can modify the same data. In basic filesystem files or folders, only one lock at a time can be set, restricting the usage to one process only. Databases, on the other hand, can set and hold mutiple locks at the same time on the different level of the physical data structure. How locks are set, last is determined by the database engine locking scheme based on the submitted SQL or transactions by the users. Generally speaking, no activity on the database should be translated by no or very light locking.

For most DBMS systems existing on the market, locks are generally shared or exclusive. Exclusive locks mean that no other lock can acquire the current data object as long as the exclusive lock lasts. Exclusive locks are usually set while the database needs to change data, like during an UPDATE or DELETE operation.

Shared locks can take ownership one from the other of the current data structure. Shared locks are usually used while the database is reading data, during a SELECT operation. The number, nature of locks and time the lock holds a data block can have a huge impact on the database performances. Bad locking can lead to disastrous performance response (usually the result of poor SQL requests, or inadequate database physical structure)

Default locking behavior is enforced by the isolation level of the data server. Changing the isolation level will affect how shared or exclusive locks must be set on the data for the entire database system. Default isolation is generally 1, where data can not be read while it is modified, forbidding to return "ghost data" to end user.

At some point intensive or inappropriate exclusive locking, can lead to the "dead lock" situation between two locks. Where none of the locks can be released because they try to acquire resources mutually from each other. The Database has a fail safe mechanism and will automatically "sacrifice" one of the locks releasing the resource. Doing so processes or transactions involved in the "dead lock" will be rolled back.

Databases can also be locked for other reasons, like access restrictions for given levels of user. Some databases are also locked for routine database maintenance, which prevents changes being made during the maintenance. See "Locking tables and databases" (section in some documentation / explanation from IBM) for more detail.) However, many modern databases don't lock the database during routine maintenance. e.g. "Routine Database Maintenance" for PostgreSQL.

Applications of databases

Databases are used in many applications, spanning virtually the entire range of computer software. Databases are the preferred method of storage for large multiuser applications, where coordination between many users is needed. Even individual users find them convenient, and many electronic mail programs and personal organizers are based on standard database technology. Software database drivers are available for most database platforms so that application software can use a common Application Programming Interface to retrieve the information stored in a database. Two commonly used database APIs are JDBC and ODBC.

Examples of use

The largest statistical database maintained by the central authority of statistics in Denmark is called StatBank. The very large database in English is available free-of-charge for all users on the internet. It is updated every day 9.30 am (CET) and contains all new statistics in a very detailed form. The statistics can be presented as cross-tables, diagrams or maps. There are about 2 million hits every year (2006). The output can be transferred to other programs for further compilation.

See also

  • Comparison of relational database management systems
  • Comparison of database tools
  • Database-centric architecture
  • Database theory
  • Government database
  • In-memory database
  • Object database
  • Document-oriented database
  • Online database
  • Real time database
  • Relational database
  • Data hierarchy


Further reading

  • O'Brien, James. "Management Information Systems". New York 1999
  • Connolly, Thomas and Carolyn Begg. Database Systems. New York: Harlow, 2002.
  • Date, C. J. An Introduction to Database Systems, Eighth Edition, Addison Wesley, 2003.
  • Galindo, J.; Urrutia, A.; Piattini, M. Fuzzy Databases: Modeling, Design and Implementation (FSQL guide). Idea Group Publishing Hershey, USA, 2006.
  • Galindo, J., Ed. Handbook on Fuzzy Information Processing in Databases. Hershey, PA: Information Science Reference (an imprint of Idea Group Inc.), 2008.
  • Gray, J. and Reuter, A. Transaction Processing: Concepts and Techniques, 1st edition, Morgan Kaufmann Publishers, 1992.
  • Kroenke, David M. Database Processing: Fundamentals, Design, and Implementation (1997), Prentice-Hall, Inc., pages 130-144.
  • Kroenke, David M. and David J. Auer. Database Concepts. 3rd ed. New York: Prentice, 2007.
  • Lightstone, S.; T. Teorey and T. Nadeau, Physical Database Design: the database professional's guide to exploiting indexes, views, storage, and more, Morgan Kaufmann Press, 2007. ISBN 0-12369-389-6.
  • Shih, J. "Why Synchronous Parallel Transaction Replication is Hard, But Inevitable?", white paper, 2007.
  • Teorey, T.; Lightstone, S. and Nadeau, T. Database Modeling & Design: Logical Design, 4th edition, Morgan Kaufmann Press, 2005. ISBN 0-12-685352-5
  • Tukey, John W. Exploratory Data Analysis. Reading, MA: Addison Wesley, 1977.

External links