Infoworks.io announced Infoworks Replicator 4.0, enabling migration of on-premises Hadoop data lakes to the cloud three times faster with one-third the resources required of traditional approaches.
Digital transformation is a critical imperative for enterprises, migrating data and analytics to the cloud is an essential step.
Automation enables rapid migration with fewer specialized resources
Infoworks Replicator makes obsolete hand-coding and labor-intensive legacy point tool processes to enable cloud data migration with fewer specialized resources, at lower cost. By automating the process, data and metadata are rapidly migrated, and scarce expensive data talent is freed to focus on higher-value business priorities.
Continuous synchronization ensures seamless migration
Replicator runs as a service, maintaining continuous operation and synchronization between on-premises Hadoop and cloud clusters to ensure consistency and continuity. Replicator enables migrations of petabytes of data without risk of data loss or business disruption; automated error handling and fault tolerance mitigate the impact of network and node failures for seamless migration.
“Our differentiated approach to high-speed computation of changes and differences between the on-premises Hadoop cluster and the cluster in the cloud changes the game. We rethought the approach to data migration to meet modern needs of scale and speed which were previously unachievable,” said Amar Arsikere, Infoworks Chief Product Officer, CTO and co-founder. “Automation is essential to the success of any large-scale data migration.”
Designed for today’s modern cloud data platform
Infoworks solves for the hurdles businesses face in cloud data and workload migration. Designed for large-scale hybrid and multi-cloud environments, Infoworks Replicator is extensible to the full Infoworks Platform. Infoworks provides customers a comprehensive solution for establishing a modern automated data platform – enabling agility, scale, and simplicity from initial cloud migration to subsequent enterprise-wide data operations and orchestration.