Overview
Big Data Integration for the Modern Enterprise
"What we love about Kapow Software is our ability to rapidly test and prototype new ideas in a matter of minutes without having to wait weeks… this allows us to quickly identify the best new features and services for our customers that we can then build for deployment very easily with the Kapow Enterprise platform."
– Volkswagen Group of America, Electronics Research Laboratory
At Kapow Software, we are resetting expectations for Big Data integration. Big Data integration projects can be completed in days instead of months with Kapow Software – even in environments where traditional integration technologies fail due to incompatible data formats or missing APIs.
This disruptive approach to Big Data integration enables you to quickly realize time-to-value from your data. Our platform also delivers the power of data integration directly into the hands of your business user, helping you foster a data-driven culture.
Kapow Enterprise Platform
The Kapow Enterprise platform enables data integration with distributed data sources and applications in a heterogeneous environment. Using Synthetic APIs™, you can integrate data or standard APIs with internal, customer, partner and supplier applications – regardless of whether existing APIs are available.
Using Kapow Katalyst™, the Kapow Enterprise integration engine, you can also easily deliver lightweight web apps called Kapow Kapplets™ that enable business users to customize and run automated data integration workflows. The business user can access and select their Kapplets via a shared library called KappZone™.
The Kapow Enterprise Platform is a secure, scalable platform composed of three main layers:
- Integrate
- Bidirectional integration with applications and data sources, without the need for APIs or connectors.
- Build
- A visual IDE used to easily build workflows for acquiring, transforming, migrating and distributing data.
- Deliver
- Automated workflows for consumption by applications, APIs, middleware or directly by users.
