Infoworks Launches Dynamic Data Warehousing Platform on Hadoop

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infoworks-logoInfoworks, a pioneering company in automated big data management announced the launch of its Dynamic Data Warehousing (DDW) platform and a complete solution to data warehouse augmentation. Infoworks separately announced that it recently closed on $5M in Series A funding.

The Infoworks DDW platform is the only automated software platform that enables enterprises to efficiently support all analytics use cases on a single Hadoop cluster. A complete solution to the problem of data warehouse augmentation is the first in a series of solutions to high-priority enterprise use-cases that Infoworks will build and release upon the DDW platform.

Enterprises today are challenged by the rapidly growing number of analytics use cases and the increasing volume and variety of data,” said Amar Arsikere, CEO and co-founder of Infoworks. “Existing methodologies and systems are proving to be too slow, inflexible, and expensive to meet these emerging needs.”

Through automation and flexible data organization, the DDW platform addresses these challenges and dramatically reduces the time to analytics insights for new use cases, while also reducing the need for specialized expertise.

The DDW platform:

  • Automatically crawls enterprise databases
  • Automatically ingests data into Hadoop and keeps it continuously synchronized
  • Organizes the data into flexible, high performance data warehouses, cubes and other data models to support a multitude of enterprise use-cases
  • Supports high performance, concurrent and interactive access for users

A complete solution for Data Warehouse Augmentation

As data volumes increase and support for new data types and new analytics are needed, traditional data warehouses are proving to be too expensive and cumbersome to handle the growth. Hadoop offers a cost-effective alternative as a repository of data that extends and augments traditional data warehouses. This approach is growing in popularity and has been termed “data warehouse augmentation” (DWA).  However, augmenting data warehouses with Hadoop presents a number of challenges in supporting enterprise requirements such as data ingestion, incremental synchronization, concurrent interactive access, data retention and security management, along with the on-going scarcity of skilled resources.

The Infoworks data warehouse augmentation solution, which is built upon the DDW platform, was developed in close collaboration with a Fortune 10 retailer. The DWA solution enables enterprises to prepare and organize all data for high-performance analytics.  The solution continuously synchronizes with existing data warehouses, while managing security and data retention policies.  The DWA solution’s built-in automation enables enterprises to rapidly modernize their analytics infrastructure without needing hard-to-find skills.

Infoworks is changing the way the enterprise works with Hadoop,” said Arsikere.  “The Infoworks DDW enables interactive, and concurrent use of Hadoop, and thereby enables enterprises to leverage the benefits of Hadoop in a large-scale production setting.”

Emerging from stealth mode

Infoworks has been in stealth mode for the past year, working with customers to develop and test the DDW platform.

Arsikere was previously responsible for designing and building a data warehousing platform on Bigtable at Google, and a petabyte scale in-memory data infrastructure at Zynga. Realizing that there is a broader need for a solution for enterprises to manage data warehousing on Hadoop, in 2014, Amar teamed up with Buno Pati, Chairman of Infoworks and an experienced entrepreneur, CEO, and investor, in founding Infoworks.

Infoworks’ innovative approach to data management, and the dramatic speed at which data can be organized and delivered for business analytics has attracted marquis customers to the DDW platform.

The DDW platform was able to help a Fortune 10 retail customer ingest 40 data sources, build six data warehouses and cubes in less than two days – a feat could take several months using traditional methods,” said Arsikiere.


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