ON DEMAND Webinar
Moving Data at the Speed of InnovationRiverbed Data Express Service
Turn Data Transfer Time from Months Into Days, Hours Into Minutes
In the age of AI-driven transformation, data is no longer just an asset — it’s the lifeblood of innovation. Riverbed Data Express is a secure platform for easily, quickly and reliably moving massive datasets across clouds, regions, and GPU environments—without operational complexity, unsustainable expense or egress surprises. It enables petabyte-scale data movement with assurance for AI, ML, and cloud migration workloads while dramatically reducing cloud data transfer costs.
Built for AI teams moving training data between AWS®, Oracle® Cloud, Azure® and GPU clusters, watch this webinar and learn how Data Express can:
Data Express currently supports AWS®, Azure®, Oracle® Cloud and Apace Airflow®

Watch this short demo to see how you can easily move petabyte-scale data across clouds with Data Express, eliminating the time and complexity of traditional data transfer solutions. Discover how you can accelerate data for AI projects, cloud migrations and GPU workloads in minutes.
With enterprise-grade security and post-quantum encryption support, Data Express is the ideal solution to move hundreds of terabytes to petabytes of data between clouds, data centers, and GPU clusters. Whether you are feeding data-starved AI models across clouds or migrating between data centers or cloud providers, Data Express :
Start Your free trial nowGet your Free Trial to see for yourself how you can easily move your massive data sets up to 10x faster.
Traditional cloud data transfer tools struggle to support AI‑scale, multi‑cloud data movement, often introducing slow performance, prohibitive Organizations relying on Rsync and Rclone often discover that “free” data movement comes with significant hidden costs.
Rsync struggles with large-scale cloud data transfers, lacks centralized visibility, requires manual scripting, and can be vulnerable to costly synchronization mistakes. While Rclone adds flexibility across multiple cloud providers, it also introduces operational risk and complexity through unknown completion time, command-line administration, extensive tuning requirements, backend-specific inconsistencies, and challenging performance optimization.
Together, these DIY approaches can consume valuable engineering resources, extend migration timelines, increase compliance and operational risk, and create costly “double bubble” scenarios where organizations pay for both source and destination environments while waiting for critical data to move.
Learn more: The Hidden Cost of DIY Data Movement