Data Warehouse Engines handle storage, quering and load mechanisms of large database.  It is an undisputable fact that implementing a data warehouse is such a very challenging task. This becomes even more challenging and difficult to do when we take into consideration the diversity of both operational data sources and target data warehouse engines. Both target and source data engines may be totally different when it comes to semantics such as considerations with regards to core data models.

Also, they may be totally different in the aspects of infrastructure such the operational details on data extraction and importation. When there is no common and sharable descriptions for both the structures of data sources and target data warehouse engines when result in having acquisition of more data warehousing tools.

A research has shown that a fifty percent growth is record every year when in comes to the amount of data that business organizations retain to be used for analytic purposes. In some other industries such those in e-commerce, the web, telecommunications, retail and governments, the growth rate figure may even be higher. These increasing trends show that there is a need for more powerful data warehouse engines.

From just a couple of years ago when data needed to power business intelligence were just stored in a central warehouses and a few other data sources within the departments, now there are countless ways to deal with high volumes of data with a multitude of data sources coming from wide geographical locations.

There are many kinds of data warehouse engines. Some of these data engines are specific to relational database implementations while some are open and can be used by any implementing database software.

Micro-Kernel Database Engine is used by Btrieve database developed by Pervasive. This database engine uses module method to separate the backend of a database from the interface used by developers. The core operations such as update, write and delete records of the database are separated from from the Btrieve and Scalable SQL modules. By doing such, programmer can use several methods of accessing the database simultaneously.

Microsoft uses the Jet Database Engine many of its products. The Jet, which stands for Joint Engine Technology, had its first version developed in 1992 which consisted of three modules for manipulating a database. The Jet is used for databases dealing with lower volume of data.

For database engines that deal larger volumes of data processing, Microsoft provided Microsoft Desktop Engine (MSDE). This was later followed by SQL Server Express Edition and most recently by SQL Server Compact Edition. However, the Jet can be upgraded to SQL Server.

InnoDB is a storage engine used by MySQL and is included in current binaries distributed by MySQL AB. It features an ACID-compliant support for transactions as well as declarative referential integrity. When Oracle acquired Innobase Oy, InnoDB became a product of Oracle Corporation. But InnoDB is dual license as it is also distributed under the GNU General Public License.

MyISAM is MySQL’s default storage engine and is a non-transactional high performance storage engine which as originally developed for data warehouse applications. Based on an older ISAM code, the MyISAM today has many new and useful extensions. MyISAM today is also one most commonly used data warehouse engines.

Data warehouse engines vary depending on the needs of the organization. But it is common today to acquire data warehouse engines that can handle the needs of very big, terabyte-scale business intelligence applications. This will make organizations get faster information to help then achieve success in the competition.