Life Sciences and Medical Research Institutions Turn to Qumulo

Qumulo, Inc. announced that life sciences and medical research institutions are choosing the company to accelerate their data-intensive workflows, including cancer and infectious disease research, genomics, bioinformatics, proteomics, microscopy and big data.

Johns Hopkins Genomics (including the NIH CIDR Program at The Johns Hopkins University, the Center for Infectious Disease Research, Georgia Cancer Center at Augusta University, Channing Division of Network Medicine at Brigham and Women’s Hospital, Progenity, Inc., and DarwinHealth, Inc. have joined the number of customers turning to Qumulo to speed discovery of new medical breakthroughs.

“Workflows in life sciences are characterized by massive volumes of machine-generated file data pipelined into downstream processes for analysis,” said Peter Godman, co-founder and CTO, Qumulo. “The rapid growth of file-based storage and processing requirements compounded by limited IT resources has created a scalability crisis for life sciences and medical research organizations. Efficient, high-performance processing of file-based data is at the heart of innovation and discovery in life sciences – something legacy file storage cannot provide. Qumulo has become the clear answer for data-intensive life sciences workflows.“

Qumulo accelerates data-intensive workflows in life science and medical research including cancer and infectious disease research and microscopy. Analysis of tissue and cancer tumor studies generates millions to billions of small files, and the expanding bio-repository file data requirements are outgrowing the capacity of legacy storage. Qumulo’s scale-out storage provides researchers with faster analysis times and IT staff with real-time visibility and control at scale.

The performing, cost-effective storage platform allows for a single file system to be shared across groups to prevent long wait times previously associated with sharing large data sets among groups. Qumulo is a replacement for legacy scale-out storage architectures that cannot keep up with modern data requirements.

Ron Hood, director of IT, the Center for Infectious Disease Research, said: “Qumulo Core’s modern architecture is built for the future and that’s what closed the deal for us. We didn’t want to spend our budget on legacy scale-out storage systems that are obsolete or will be in two to three years. Qumulo supports our needs today and well into the future, so that we can achieve faster times to analysis for our most critical research.“

Microscopy systems often generate image data sets as large as 1TB per experiment. Those images are stored and accessed for processing and analysis from client computers running OSs such as Windows, macOS and Linux. The sequencing data is a widely varied collection of files ranging in size from a few kilobytes, often numbering in the millions to billions, up to large image files that can be 50GB each. Qumulo is a solution for this workload, providing scalability, performance, fast access to files across the entire range for processing and analysis, storage of billions of files and support for mixed file workloads.

Qumulo Core was designed for the era of multi-petabyte data scale on premises and in the cloud. It stores tens of billions of files with scalable throughput and is the only product that provides real-time visibility and control for file systems at petabyte scale. Storage administrators and life sciences researchers can instantly see usage, activity and throughput at any level of the unified directory structure, no matter how many files in the file system, allowing them to pinpoint problems and manage how storage is used by analysis pipelines. In addition, a Qumulo Core storage cluster can be installed and deployed in minutes without specialized IT expertise.

Publicly announced life sciences customers include: Carnegie Institution for Science, CID Research, Channing Division of Network Medicine at Brigham and Women’s Hospital, DarwinHealth, Inc., Georgia Cancer Center at Augusta University, Institute for Health Metrics and Evaluation (IHME) at University of Washington, Johns Hopkins Genomics at The Johns Hopkins University, Progenity, Inc., UConn Health, University of Utah Scientific Computing and Imaging (SCI) Institute.