Actian provides Customers Open, Enterprise Grade SQL Analytics Access to Their Hadoop Data
Actian provides Customers Open, Enterprise Grade SQL Analytics Access to Their Hadoop Data : Actian, the company to bring lightning fast, full ANSI SQL 92 compliant access natively in Hadoop, has expanded its open footprint so customers can benefit from the power of the highest performing and fully industrialized SQL in Hadoop without risking vendor lock-in. Actian Vortex has opened Hadoop to millions of SQL programmers from Bangalore to San Francisco and to popular SQL-based business intelligence tools like MicroStrategy, Tableau and Yellowfin. Actian’s collaborative architecture allows customers to query native Hadoop file formats like Parquet and ORC without requiring complex ingestion and provides open access to Actian’s block formats to achieve maximum performance, scale, flexibility, and security. Hadoop is unrivalled as a cost-effective and super-scaling data reservoir. But, as with any young technology, it is plagued with performance challenges and lack of available skilled resources. Actian has focused relentlessly on providing any Hadoop data lake with an open, enterprise-grade analytics engine to accelerate Hadoop adoption, business solutions and time to revenue.
“Actian Vortex has essentially averted the analytical skills crisis for Hadoop customers by providing the only enterprise grade, full SQL analytics engine for Hadoop. Now, we are focusing on solving the infrastructure skills shortage for managing enterprise-scale Hadoop solutions,” said Ashish Gupta, Actian chief marketing officer and senior vice president of business development. “By providing access to popular Hadoop file formats, Actian has erased ingestion challenges and with native support for popular open source management tools, Actian has eased Hadoop adoption challenges. Our customers can now focus on solving the stickiest business challenges – from cybersecurity to risk management with Hadoop-based solutions that are complemented by Actian Vortex.”
In head-to-head comparisons with SQL-on-Hadoop offerings like Cloudera Impala, Actian has outperformed in analytic processing time by up to 30x. By pairing raw performance with full SQL ANSI support, ACID-compliance, and full DBMS security and authentication, users can query Hadoop data using standard BI and reporting tools. It enables real-time trickle updates, making it possible for the first time to easily correct and update data in Hadoop while still running high-performance analytics on the data. Actian makes it possible to avoid vendor lock-in by being Hadoop-distribution agnostic, providing open APIs and supporting open file formats. SQL programmers and business analysts have powerful productivity and accuracy breakthroughs while making high science analytics consumable, accessible and reusable.
“Actian has a multi-year technology lead on other products in the market today, thanks to our enterprise-hardened technology that has been built from the ground up to run natively in Hadoop,” said Mike Hoskins, Actian chief technology officer. “We’ve opened the Hadoop floodgates to SQL programmers and business analysts, fundamentally removing the skills gap from the Hadoop adoption equation. Now, organizations can turn their attention to the next big data dilemma – being bold enough to change the status quo and infuse Hadoop analytics into every facet of their business.”
Actian transforms big data into business value for organizations of all sizes, no matter where they are on their analytics journey. Actian help companies win by empowering them to connect to data of any type, size or location; analyze it quickly wherever it resides; and take immediate action on accurate insights gained to delight their customers, gain competitive advantage, manage risk and find new sources of income. With the Actian Analytics Platform, it delivered the world’s first end-to-end analytics platform built to run 100 percent natively in Hadoop. Among tens of thousands of organizations using Actian are innovators in the financial services, healthcare, telecommunications, digital media and retail industries.
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More Information on Predictive Analysis Process
For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.