Syncsort, the global leader in Big Iron to Big Data software, today announced it has acquired SQData, an Addison, Texas-based provider of enterprise-class data integration technology. The acquired products and expertise will advance Syncsort’s ability, through its Syncsort Connect portfolio, to help customers unlock the full value of critical mainframe data by making it easier to integrate that data with emerging technologies.
“Nearly all of our 7,000 customers need to leverage decades of investment in legacy data systems by integrating these critical data assets with Next Wave technologies such as hybrid cloud, blockchain and streaming,” said Josh Rogers, CEO, Syncsort. “SQData has been a strategic technology partner, contributing to our leadership in addressing this challenge with mainframe data. Bringing their high-performance data replication technology and skills in-house will enhance our ability to deliver real-time solutions for critical customer use cases, enabling predictive analytics, machine learning and AI.”
Building on Syncsort’s existing support for VSAM and Db2/z data, the SQData acquisition brings new capabilities for IBM IMS. Despite processing billions of transactions a day, IBM IMS is often overlooked for enterprise analytics due to its complexity and potential performance impact. SQData’s proven technology will be used to stream data from IMS for downstream analytics, with minimal impact on processing speed and efficient delivery of information to business users.
The SQData acquisition closely follows Syncsort’s launch of Connect CDC, which enables companies to build streaming data pipelines for real-time sharing of mainframe and other data sources. Connect CDC allows customers to publish data from legacy systems to streaming frameworks such as Kafka and next generation repositories such as Hadoop and cloud data lakes. It is the latest example of the type of innovation being driven from the recently announced Syncsort Invent Initiative, which invites data-driven enterprises to work with Syncsort to solve their most complex data challenges that result from trying to integrate legacy systems with Next Wave technologies.