Database is a collection of information organized and presented to serve a specific purpose. A computerized database is an updated, organized file of machine readable information that can be is rapidly searched and retrieved by a computer. The term database is often misused as a synonym for a database management system (DBMS). They are not equivalent. A database management system is the software mechanism for managing that data.
A DBMS can be viewed as a more sophisticated and flexible form of file management together with a flexible tool for data extraction and often other "high level" tools. The main types of DBMS are:
Relational Database - It is the most popular type of DBMS implemented. A Relational DBMS use the Structured Query Language (SQL) to extract and update data and conform as closely as possible to the theoretical relational rules of normalization. Work best when the data structures have been "normalized" to eliminate data and field duplication. Data is organized within "Tables" (files) and relationships expressed between tables and data elements. SQL is now the industry standard for data querying and updating of databases.
Multi-Dimensional Database - Unlike Relational databases which store data in a two dimensional format, where tables of data are presented as rows and columns, Multi-dimensional database systems provide a multi-dimensional view of the data (Rand). For example, in multi-dimensional analysis, data entities such as products, regions, customers, dates etc. may all represent different dimensions. This database model has the ability to analyse large amounts of data with very fast response times, and can "slice and dice" through data, and "drill down or roll up" through various dimensions of the defined data structure. The Multi-dimensional database, together with the processing tool OLAP (Online Analytical Processing), form the foundation of data warehousing and data mining.
Text Retrieval Systems or "Free Form" Databases - Free Form databases have no structure, just the opposite the relational database. The main advantage is the power of search and retrieve functions. Where there are large numbers of technical reports to be searched for information in an unpredictable way then a text retrieval engine is required since its efficiency and flexibility of indexing mean that you can index the "full text" of the report. A text retrieval engine verges on textual analysis. The search sophistication possible with such indexes is enormous - Boolean combinations between terms both within and across fields are simply done and the typical text retrieval functions of adjacency, truncation, set manipulation etc are all built in.
Object Oriented DBMS (OODBMS) - Object orientation for a database means the capability of storing and retrieving objects in addition to mere data. As their name suggests - Database Management Systems were designed to look after data - numbers, words etc. Objects are complex and not well handled by standard Relational DBMS. Object Oriented DBMS have
been emerging and major vendors like Oracle have announced object capability in their products. Most OODBMS systems can handle images, video and other objects.
Hybrids - There are hybrid systems and hybrid databases. Basically, a hybrid system is one that uses two DBMS. For example, a text retrieval engine can be combined with a structured DBMS to produce the best of both worlds.
Others database models
Nested - These systems are all derived from the PICK system developed by Dick Pick and IBM in the late 60s/early 70s. The original PICK system was designed as a database cum operating system with the tools for data retrieval built in like the relational DBMS. However, the PICK-like "nested" or "post relational" systems allow related multiple values and sub values within a field - groups of related data and easily support variable length, non-limited fields.The data query language although easier to use than SQL was "not SQL" and associated tools for data querying could not be used against a Nested DBMS. Now both main Nested Relational DBMS suppliers can be queried using SQL. It is not deployed widely.
Hierarchical - Now obsolete, a hierarchical DBMS assumed hierarchical relationships between data i.e. parent - child. Data structures were often forced to conform to the hierarchical model in order to take advantage of the management and programming aspects of the products.
Network - Network DBMS allowed complex data structures to be built but were inflexible and required careful design. It is very efficient in storage and fast. Best examples are airline booking systems. It is now obsolete.
Mumps - Mumps was developed in the 1970s for use in the Health sector for very large on-line databases with an emphasis on transaction processing. It can handle relational, network or hierarchical data models. The database management functions are closely coupled with the application language and as a result Mumps is a very fast and efficient database management environment.
AS/400- The AS/400 series of minicomputers from IBM comes bundled with a DBMS as part of the operating environment -OS/400. The system is very powerful and flexible - has similarities to the Nested Relational DBMS model - allowing relational database structures and has a simple to use database enquiry facilities for ad-hoc reporting.
Related Terms: OLAP, Data Warehouse, Data Mining, Relational Database, Multi-Dimensional Database, OODBMS