The sheer volume of data being produced for genomics research is beyond astronomical—literally.
The sheer volume of genomics data is doubling every 7 months. By 2025, the capacity needed for genomics data is estimated to reach 40 exabytes (40,000 petabytes) exceeding that for astronomical data by a factor of up to 40:1.
Driving this growth are more advanced sequencers like those from Pacific Biosciences, as well as the mainstreaming of personalized medical treatments.
Pacific BioSciences manages 700% YOY storage capacity growth
Watch how Pacific BioSciences, a genomics leader, used Komprise to transform how they manage genomic test data and 700% YOY storage capacity growth.
Genomic Data Needs to Stay Accessible
The greater the volume of genomics data available the more valuable the sum of that data becomes. Also, the retention and accessibility of this data is necessary to comply with mandates such as the Individual Right to Access in HIPPA or those specified in research grants and by individual studies.
The challenge is how to store and manage this explosion of genomics data in an era of tight IT budgets, especially in academic and research organizations. The traditional approach of moving this data offline to a cost effective archival storage simply does not address the needs of genomics data and as a result the vast majority of this data is still residing on expensive, high performance, Network Attached Storage.
Using Komprise to create and active archive for genomics data offers the cost effectiveness of moving cold data to archival storage solutions while retaining file based access to users and applications so that to end users the data appears as if it is on NAS providing the best of both worlds.
Komprise will be at Bio-IT World the next week (May 15th – 17th) demonstrating how our customers are managing their explosive growth and giving architecture presentations at our booth #413. We will also be presenting sessions at the Google Booth #413 Wednesday 5/16 at 10:30am, 1:30pm and again at 4:00pm.
If you are headed to Bio-IT World, let us know!
(Source: Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, et al. (2015) Big Data: Astronomical or Genomical?. PLoS Biol 13(7): e1002195. doi:10.1371/journal.pbio.10021)