Main article: Database management system
A database management system (DBMS) consists of software that operates databases, providing storage, access, security, backup and other facilities. Database management systems can be categorized according to the database model that they support, such as relational or XML, the type(s) of computer they support, such as a server cluster or a mobile phone, the query language(s) that access the database, such as SQL or XQuery, performance trade-offs, such as maximum scale or maximum speed or others. Some DBMS cover more than one entry in these categories, e.g., supporting multiple query languages.
[edit] Components of DBMS
Most DBMS as of 2009 implement a relational model.[2] Other DBMS systems, such as Object DBMS, offer specific features for more specialized requirements. Their
components are similar, but not identical.
[edit] RDBMS components
• Sublanguages— Relational DBMS (RDBMS) include Data Definition Language (DDL) for defining the structure of the database, Data Control Language (DCL)
for defining security/access controls, and Data Manipulation Language (DML) for querying and updating data.
• Interface drivers—These drivers are code libraries that provide methods to prepare statements, execute statements, fetch results, etc. Examples include ODBC, JDBC, MySQL/PHP, FireBird/Python.
• SQL engine—This component interprets and executes the DDL, DCL, and DML statements. It includes three major components (compiler, optimizer, and
executor).
• Transaction engine—Ensures that multiple SQL statements either succeed or fail as a group, according to application dictates.
• Relational engine—Relational objects such as Table, Index, and Referential integrity constraints are implemented in this component.
• Storage engine —This component stores and retrieves data from secondary storage, as well as managing transaction commit and rollback, backup and recovery, etc.
[edit] ODBMS components
Object DBMS (ODBMS) has transaction and storage components that are analogous to those in an RDBMS. Some ODBMS handle DDL, DCL and update tasks differently.
Instead of using sublanguages, they provide APIs for these purposes. They typically include a sublanguage and accompanying engine for processing queries with interpretive statements analogous to but not the same as SQL. Example object query languages are OQL, LINQ, JDOQL, JPAQL and others. The query engine returns collections of objects instead of relational rows.
[edit] Types
[edit] Operational database
These databases store detailed data about the operations of an organization. They are typically organized by subject matter, process relatively high volumes of updates using transactions. Essentially every major organization on earth uses such databases.
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, manufacturing databases that record details about product components, parts inventory, and financial databases that keep track of the organization's money, accounting and financial dealings.
[edit] Data warehouse
Data warehouses archive historical data from operational databases and often from external sources such as market research firms. Often operational data undergoes transformation on its way into the warehouse, getting summarized, anonymized,
reclassified, etc. 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 use UPC codes so that it can be compared with ACNielsen data.
[edit] Analytical database
Analysts may do their work directly against a data warehouse, or create a separate analytic database for Online Analytical Processing. For example, a company might extract sales records for analyzing the effectiveness of advertising and other sales promotions at an aggregate level.
[edit] 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.
[edit] End-user database
These databases consist of data developed by individual end-users. Examples of these are collections of documents in spreadsheets, word processing and downloaded files, or even managing their personal baseball card collection.
[edit] External database
These databases contain data collect for use across multiple organizations, either freely or via subscription. The Internet Movie Database is one example.
[edit] Hypermedia databases
The Worldwide web can be thought of as a database, albeit one spread across millions of independent computing systems. Web browsers "process" this data one page at a time, while web crawlers and other software provide the equivalent of database indexes to support search and other activities.
[edit] Models
Main article: Database model
[edit] Post-relational database models
Products offering a more general data model than the relational model are sometimes classified as post-relational.[3] Alternate terms include "hybrid database", "Object-enhanced RDBMS" and others. The data model in such products incorporates relations but is not constrained by E.F. Codd's Information Principle, which requires that
all information in the database must be cast explicitly in terms of values in relations and in no other way[4]
Some of these extensions to the relational model 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 post-relational products extend relational systems with non-relational features.
Others 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.
[edit] Object database models
Main article: Object database
In recent years, the object-oriented paradigm has been applied in areas such as
engineering and spatial databases, telecommunications and in various scientific domains.
The conglomeration of object oriented programming and database technology led to this new kind of database. 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 key ideas of object programming, such as encapsulation and polymorphism, into the world of databases.
A variety of these ways have been tried[by whom?] for storing objects in a database. Some products have approached the problem from the application-programming side, 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 provide language-level functionality for finding objects based on their information content. Others[which?] 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.