How Decentralization Delivers High Performance for Big Data

With today’s traditional hyperscalers, resilient and performant cloud storage is possible but at quite a price—both in terms of budget and administrative resources. To use this centralized model, a balance between these factors and acceptable costs must be achieved. Why not try something different and better? Decentralized and distributed networks enable multi-layered parallelism and resiliency that delivers incredible throughput. In this edge-based performance model, files are uploaded and broken up into segments and pieces, then distributed on a global network of more than 13,500 Storage Nodes. This means your speed limit is gated only by your local compute or network resources and that you can positively impact multiple performance metrics such as IOPS, latency, RTO, Ingress/Egress, and etc. Join us for this Let’s Talk Storj DCS Webinar - How Decentralization Delivers High Performance for Big Data. In this installment, Storj COO, John Gleeson, Storj Systems Engineer, Dominick Marino, and University of Edinburgh Research Explorer, Dr. Antonin Portelli, will discuss how the increased parallelism, redundancy, and resiliency of emerging decentralized technologies are fundamental for big data. Attend the webinar to learn how: - Multi-threaded concurrent downloads and uploads of a file provide faster performance and efficiency via parallel, peer-to-peer transfer - Key tools and integrations can help fine tune your performance - This approach is being used today to accelerate large file distribution - All these benefits are built-in and cost up to 80% less than traditional hyperscalers Also learn more about an independent study by the University of Edinburgh that validated this performance and proved fundamental for the large data sets stored and accessed in their scientific research.