IBM InfoSphere DataStage



IBM InfoSphere DataStage is an ETL tool and part of the IBM Information Platforms Solutions suite and IBM InfoSphere. It uses a graphical notation to construct data integration solutions and is available in various versions such as the Server Edition and the Enterprise Edition.

A data extraction and transformation program for Windows NT/2000 servers that is used to pull data from legacy databases, flat files and relational databases and convert them into data marts and data warehouses. Formerly a product from Ascential Software Corporation, which IBM acquired in 2005, DataStage became a core component of the IBM WebSphere Data Integration suite.

DataStage originated at VMark[1], a spin off from Prime Computers that developed two notable products: UniVerse database and the DataStage ETL tool.


The first VMark ETL prototype was built by Lee Scheffler in the first half of 1996[1].

Peter Weyman was VMark VP of Strategy and identified the ETL market as an opportunity. He appointed Lee Scheffler as the architect and conceived the product brand name "Stage" to signify modularity and component-orientation[2].

This tag was used to name DataStage and subsequently used in related products QualityStage, ProfileStage, MetaStage and AuditStage.

Lee Scheffler presented the DataStage product overview to the board of VMark in June 1996 and it was approved for development.

The product was in alpha testing in October, beta testing in November and was generally available in January 1997.

VMark acquired UniData in October 1997 and renamed itself to Ardent Software[3]. In 1999 Ardent Software was acquired by Informix[4] the database software vendor.

In April 2001 IBM acquired Informix and took just the database business leaving the data integration tools to be spun off as an independent software company called Ascential Software[5].

In November 2001, Ascential Software Corp. of Westboro, Mass. acquired privately held Torrent Systems Inc. of Cambridge, Mass. for $46 million in cash.

Ascential announced a commitment to integrate Orchestrate's parallel processing capabilities directly into the DataStageXE platform. [6].

In March 2005 IBM acquired Ascential Software[7] and made DataStage part of the WebSphere family as WebSphere DataStage.

In 2006 the product was released as part of the IBM Information Server under the Information Management family but was still known as WebSphere DataStage.

In 2008 the suite was renamed to InfoSphere Information Server and the product was renamed to InfoSphere DataStage[8].

•Enterprise Edition: a name give to the version of DataStage that had a parallel processing architecture and parallel ETL jobs.

•Server Edition: the name of the original version of DataStage representing Server Jobs. Early DataStage versions only contained Server Jobs. DataStage 5 added Sequence Jobs and DataStage 6 added Parallel Jobs via Enterprise Edition.

•MVS Edition: mainframe jobs, developed on a Windows or Unix/Linux platform and transferred to the mainframe as compiled mainframe jobs.

•DataStage for PeopleSoft: a server edition with prebuilt PeopleSoft EPM jobs under an OEM arragement with PeopleSoft and Oracle Corporation.

•DataStage TX: for processing complex transactions and messages, formerly known as Mercator.

•DataStage SOA: Real Time Integration pack can turn server or parallel jobs into SOA services.




Monday, November 2, 2009


WebSphere Federation Server

WebSphere Federation Server supports the growing industry category called Enterprise Information Integration (EII).
It enables applications to access and integrate diverse data and content sources as if they were a single resource
-- regardless of where the information resides
-- while retaining the autonomy and integrity of the source systems.

The underlying principle of federation is for users to be able to see all of the data they use as if it resided at a single source. By presenting this single source image, federation technology shields the requester from all the complexities associated with accessing data in diverse locations, including connectivity, semantics, formats, and access methods. The middleware enables users, or applications acting on their behalf, to access information transparently without concern for its physical implementation.

Consequently, WebSphere Federation Server fits neatly and transparently behind common analytical and reporting tools; development environments; portals; and other standard IT infrastructure components.

With WebSphere Federation Server, you can send distributed requests to multiple data sources within a single SQL statement; for example, you can join data that is located in a DB2 table, an Oracle table, and an XML tagged file in a single SQL statement. When an application submits a query to the federated system, the federated server identifies the relevant data sources, and develops a query execution plan for obtaining the requested data.

The plan typically breaks the original query into fragments that represent work to be delegated to individual data sources, as well as additional processing to be performed by the federated server to further filter, aggregate, or merge the data.

The ability of the federated server to further process data received from sources allows applications to take advantage of the full power of the query language, even if some of the information requested comes from data sources with little or no native query processing capability, such as simple text files. In addition to managing the federation, the federated server is also a full-function relational database with the capability to store and manage local data.

To summarize, the power of WebSphere Federation Server lies in its ability to:

>Correlate data from local tables and remote data sources, as if all the data is stored locally in the federated database.
>Update data in relational data sources, as if the data is stored in the federated database.
>Take advantage of the data source processing strengths and unique optimizations, by sending distributed requests to the data sources for processing.
>Compensate for SQL limitations at the data source by processing parts of a distributed request at the federated server.

The federated approach to achieving EII has competed with the more traditional method of data consolidation. Consolidated data stores, which are typically managed to extract, transform, load (ETL) or replicate data, are the standard choice for information integration today and have been the best way to achieve fast, highly available, and integrated access to related information. Creating a single physical copy lets businesses meet performance or availability requirements, deliver snapshots that are point-in-time consistent, and provide sophisticated transformation for semantic consistency.

Federation can help IT departments be more responsive to business needs by quickly prototyping and refining transformations, accessing up-to-the second data, delivering value-added content-rich information, such as documents and images, which it is not practical to replicate, and providing access to data that it is not possible to consolidate (for example, for compliance reasons). By combining data consolidation with federation, businesses achieve the flexibility and responsiveness that is required in today's fast paced environment.
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