SANTA CLARA, CA – May 10, 2017 — / — To keep up with the accelerating pace of innovation and discovery, life sciences IT architects need better ways to satisfy application demands and meet the operational goals of their businesses. Unfortunately, traditional storage infrastructures create data silos and performance bottlenecks that limit many crucial life science applications.

Faced with the need to perform increasingly complex analysis over massive, distributed data sets (e.g. for genomic, proteomic, or pharmaceutical research), legacy storage arrays and first-generation software-defined storage (SDS) products struggle to support the demanding data access and sharing requirements. Also, while the emergence of the public cloud has created an alternative infrastructure option, it threatens to tether crucial data within yet another expensive silo.

Modern workloads in life sciences present many IT challenges including:

  • Broadly Distributed Data – analysis for life sciences often leverages parallel processing techniques requiring simultaneous access from many users and/or applications, both on-premises and in the cloud
  • Many, Small Chunks of Data – snippets of data acquired from sensors or other measurement devices may be generated very rapidly, requiring high IOPS to ingest and serve numerous small files
  • Large Scientific Files – massive files, such as aligned genome sequences or high-resolution imaging, can be troublesome to manage and share as they outgrow the capacity of siloed storage solutions

To satisfy the challenges created by life sciences workflows, organizations should look towards software-defined, flash-native, distributed file systems capable of unifying all data within a single global namespace across on-premises and cloud environments. These file systems must provide cost-effective, scalable storage for inactive data sets and deliver consistent, transactional performance to support active access for analytics.

“Life sciences workloads on traditional storage architectures often face bottlenecks that hamper their ability to maintain rapid, consistent access to distributed scientific data, which ultimately reduces the efficiency and speed of the associated scientific research,” said Dr. Allon Cohen, Elastifile VP of Product.  “Continued advances in life sciences are reliant on the ability to overcome these bottlenecks and to enable seamless use of the best available analysis tools, which often involves leveraging the cloud and new deployment technologies such as containers.  As a result, cross-cloud data fabrics are now needed to support life sciences researchers with an agile, high-performance, global data infrastructure.”

To learn more about Elastifile’s solution for life sciences infrastructure and the benefits of a high-performance, cross-cloud data fabric, please see the following resources:

Elastifile solution brief on Parallel Computing for Life Sciences:

Elastifile blog discussing the intersection of Life Sciences research, Computer Science, and IT:

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About Elastifile
Elastifile is redefining the way data is stored and managed, enabling seamless deployment of private and hybrid cloud solutions. With enterprises and service providers increasingly looking to support both on-premises and cloud workflows, Elastifile uniquely delivers this data management to application, analytics, and infrastructure teams as the single global namespace of an application-level distributed file/object system. This elastic, scale-out, software-defined BYOH (bring-your-own-hardware) solution brings all the advantages of public IaaS to the data center and all the enterprise data services to the hybrid cloud.

Elastifile was founded in 2013 and is backed by seven market leaders from across the data center and storage industries, Battery Ventures, and Lightspeed Venture Partners. Elastifile’s founders and leadership team includes a powerful mix of experience across enterprise storage, virtualization, applications, and flash to help transform its customers’ hybrid cloud workflows.


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Source: Elastifile



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