Connecting Your Epicor Kinetic ERP & Impala Data
Whether you’re integrating Epicor Kinetic ERP with Impala or moving data from one of these solutions to the other, getting your information where it needs to be is crucial. Use StarfishETL’s robust iPaaS to connect your data with speed and flexibility.
Secure Connections Between Epicor Kinetic ERP to Impala
The iPaaS powering your Epicor Kinetic ERP and Impala connection not only provides unrivaled scalability, but also offers strict security protocols to keep data safe as it moves across applications. StarfishETL applies two-fold data security between Amazon Web and our internal servers to maintain the highest levels of protected infrastructure. Strict data encryption practices and progressive security principles keep sensitive information secure at all times as it passes between Epicor Kinetic ERP and Impala.
Epicor Kinetic ERP and Impala Integration
Integrate Epicor Kinetic ERP and Impala to boost your analytical power, align your teams, and create more omnichannel experiences across your business. StarfishETL makes the process seamless with a library of pre-configured maps at your fingertips and easy ways to customize your project. Check out the visual below to learn how a typical integration flows. Then, contact our team to request a quote on your Epicor Kinetic ERP and Impala project.
Set up access to each system
Define processes & stages
Modify integration & add custom fields
Run initial data migration load
Ensure keys are matching between systems
About These Solutions
Epicor ERP, now known as Kinetic, is a cloud-based ERP software solution designed with manufacturing in mind. Epicor ERP provides a comprehensive and fully functional online portal for managing business processes as well as accounting, finance, HR, customer relationships, and more.
Apache Impala is a modern, open-source, Massive Parallel Processing (MPP) SQL query engine used for analyzing and processing data stored in the Hadoop cluster. Impala is designed for speed and can process data stored in FDFS lightning-fast. Its interactive queries can read nearly all file formats such as Parquet, Avro, and RCFfile used by Hadoop.