DataRoket QlikView Connector

DataRoket Business Objects Data Connector for QlikView

 Many organizations have invested in multiple business intelligence and data storage solutions as part of their overall business intelligence platform. With the QlikView Connector for DataRoket, data residing in these business intelligence platforms can be seamlessly integrated into the QlikView environment, providing Business Discovery capabilities for forging new paths to insight and decision. As a leader in data integration with real-time accelerated data acquisition capabilities, DataRoket provides the ability to leverage existing information assets by integrating data from both structured and unstructured data sources into a single, easy to deploy platform. By combining DataRoket’s data integration capabilities and QlikView’s associative in-memory platform, business users can perform quick, flexible, visual, ad hoc analysis and reporting to enable Business Discovery on both structured and unstructured data sources.

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About QlikTech.

QlikTech (NASDAQ: QLIK) is a leader in Business Discovery-user-driven Business Intelligence (BI).  QlikTech’s powerful, accessible Business Discovery solution bridges the gap between traditional business intelligence solutions and standalone office productivity and applications.  Its QlikView Business Discovery platform enables intuitive user-driven analysis that can be implemented in day or weeks rather months, years or not at all.  The in-memory associative search technology it pioneers allows users to explore information freely rather than being confined to a predefined path of questions.  QlikView Business Discovery works with existing BI applications and ads new capabilities: insight for everyone, zero-wait analysis, mobility, and app-like model, remixablilyt and reassembly, and social collaborative experience.  Head quartered in Radnor, Pennsylvania, QlikTech has offices around the world serving more approximately 22,000 customers in over 100 countries.

Hadoop Connector/Adaptor            

Available as DataRoket Solution or QlikView Connector.    (Download Fact Sheet).

DataRoket’s Hadoop functionality and connector are delivered as two different connectors;

• Hadoop
• ADS File Stores

The Hadoop connector delivers the ability to access distributed Hadoop Files systems by HDFS access.   Both uncompressed and map reduce files can be accessed, queried, and rendered to XML, real time LZO compression (used within Hadoop’s wrapper to the Oburhumer C programming libraries).

-          Extract Hadoop File system or HDFS data files in uncompressed or Map Reduced state.

-          Associate and query Hadoop data directly by DataRoket’s distributed Engines (data byte correlation and in memory real time                compression with cell pointer system.

-          Sort, validate, and partition query data back into Hadoop map reduce, direct LZO compressed XML in block partitions (ie: 2-25            million Record set chunks.)

Persisted or direct in memory resident Data sets.

Ability to correlate/associate Hadoop data with any data source connector DR has available (handled at both string and byte key level)

Custom connectors such as unstructured Data Algorithms have also been developed for past customers using the DataRoket ADS ( Analytical data store) Hadoop approach.

Screensho showing DataRoket feeding Orcale data into Hive.



For example the following are two USE cases we have delivered:

1. Wachovia Mainframe derived records existing in flat file structure. DR developed a connector which looks up Composite key mappings from SQL databases which then are correlated with Wachovia flat file records based on data algorithms against relationship mapping rules.
2. PeopleSoft General Ledgers files, mixed metadata content, variable columns throughout the files.  DataRoket delivered the architecture and data algorithms which were able to read 70+ PeopleSoft general ledgers, totaling in capacity 4.6 GBs, read and sort the data amongst DR distributed engines within 7 minutes, total of 100 million+ records.

DataRoket parallel processed the data files and then based on metadata lookup associated/correlated the datasets in columnar fashion delivering LZO compressed and order datasets through Hadoop JNI wrapper.

Screenshot of Hive as a data source showing table.

Delivered as QlikView Data Pipe for seamless access through QlikView.

Futures:  Pig Tuples Handler.

DataRoket is a completely web based and OS independent application.  We have ensured that the application can be deployed via our SaaS environment or as a simple Virtual Appliance that can operate on VMWare or Xen Server.  Should a customer desire to host the application in their own traditional environment, this can be accommodated since DataRoket is not only OS independent, but is app and web-server independent.

Yes. DataRoket is the intense three year effort of former scientists from Sybase and Business Objects.

How DataRoket™ solves Four of the Core Challenges in Data Today

Instead of shying away from these four core challenges or making it the other tool’s problem, we embraced these challenges and made them the centerpiece of our platform.

DataRoket™ is a new level of combined performance, ease of deployment and usability.  DR’s parallel computing, multi-threaded processing and a patent-pending data model delivers enterprise performance and scalability on standard hardware. Below is a high level diagram of the DR solution.

DataRoket™ addresses all of these challenges, delivering real-time reporting (unparalleled performance) and breaching user limitations (proven scalability).