Kapow Software today announced its second best quarterly bookings in the company's history with new subscriptions to its Kapow Katalyst Big Data Integration platform rising more than 57 percent quarter over quarter compared to Q1-FY2013, ending September 30, 2012.

In addition, Kapow Software achieved historical highs with a 96 percent customer renewal rate and its highest-ever average selling price, up 30 percent year over year. The company's biggest Q2 revenue drivers were based on market need to consumerize big data in three key categories: transforming big data to actionable intelligence (Web intelligence), business process automation and content integration.

"No matter what industry they're in, our enterprise customers are constantly telling us they need big data solutions that deliver now, not in 24 months," says John Yapaola, CEO of Kapow Software. "They need to rapidly generate custom, automated research across a complex web of internal and external data sources that deliver valuable business insights in real time. From competitive pricing checks, brand monitoring and regulatory compliance to automation of manual processes and transactions across legacy, cloud, email, partners and suppliers. Companies of all kinds are now laser focused on creating efficiencies and margins to scale the business and drive topline growth."

Kapow aims to enable business leaders to manage the collection and integration of legacy, cloud, social and big data and visualize the results, extract value and take action. It also looks to add value without massive investments in data warehousing and data mining.

Other offerings include Kapow Katalyst, where customers can create a "synthetic API" where no API currently exists. Whereas a traditional API is created and published by the owner of the application, Kapow Software's platform can create an API with similar functionality when an API doesn't already exist or as a complement to existing API functionality. Often, using a synthetic API generated by Kapow Katalyst is faster and easier than working with existing APIs and can accelerate time to value for big data investments.