Items Tagged: IBM+Cloud
Is Object Storage Right For Your Organization?
Is object storage right for your organization? Many companies are asking this question as they seek out storage solutions that support vast unstructured data growth throughout their organizations. Object storage is ideal for large-scale unstructured data storage because it easily scales to several petabytes and beyond by simply adding storage nodes. Object storage also provides high fault tolerance, simplified storage management and hardware independence – core capabilities that are essential to cost-effectively manage large-scale storage environments. Add to this built-in support for geographically distributed environments and it’s easy to see why object storage solutions are the preferred storage approach for multiple use cases such as cloud-native applications, highly scalable file backup, secure enterprise collaboration, active archival, content repositories and increasingly cognitive computing workloads such as Big Data analytics.
To help you decide if object storage is right for your company and to help you understand how to apply various storage technologies, we have created a table below that positions object storage relative to block storage and file storage.
As the table shows, there are several factors that differentiate block, file and object storage. An easy way to think about the differences is the following; block storage is necessary for critical applications where storage performance is the key consideration, file storage is well-suited for highly scalable shared file systems and object storage is ideal when cloud-scale capacity and convenience as well as reliability and geographically distributed access are the major storage requirements.
The healthcare industry is facing tremendous data challenges as the medical community evolves to support rapid growth in digital medical imaging, new government regulations and improvements in patient care.
IBM Cloud Object Storage Provides the Scale and Integration Needed for Modern Genomics Infra.
For hospitals and medical research institutes, the ability to interpret genomics data and identify relevant therapies is key to provide better patient care through personalized medicine. Many such organizations are racing forward, analyzing patients’ genomic profiles to match more clinically actionable treatments using artificial intelligence (AI).
These rapid advancements in genomic research and personalized medicine are very exciting, but they are creating enormous data challenges for healthcare and life sciences organizations. High-throughput DNA sequencing machines can now process a human genome in a matter of hours at a cost approaching one thousand dollars. This is a huge drop from a cost of ten million dollars ten years ago and means the decline in genome sequencing cost has outpaced Moore’s Law (see chart). The result is an explosion in genomic data – driving the need for solutions that can affordably and securely store, access, share, analyze and archive enormous amounts of data in a timely manner.
Challenges include moving large volumes of genomic data from cost-effective archival storage to low latency storage for analysis to reduce the time needed to analyze genetic data. Currently, it takes days to do a comprehensive DNA sequence analysis.
Sharing and interpreting vast amounts of unstructured data to find relationships between a patient’s genetic characteristics and potential therapies adds another layer of complexity. Determining connections requires evaluating data across numerous unstructured data sources, such as genomic sequencing data, medical articles, drug information and clinical trial data from multiple sources.
Unfortunately, the traditional file storage within most medical organizations doesn’t meet the needs of modern genomics. These systems can’t accommodate massive amounts of unstructured data and they don’t support both data archival and high-performance compute. They also don’t facilitate broad collaboration. Today, organizations require a new approach to genomics storage, one that enables:
- Scalable and convenient cloud storage to accommodate rapid unstructured data growth
- Seamless integration between affordable unstructured data storage, low latency storage, high performance compute, big data analytics and a cognitive healthcare platform to quickly analyze and find relationships among complex life science data types
- A multi-tenant hybrid cloud to share and collaborate on sensitive patient data and findings
- Privacy and protection to support regulatory compliance
Cloud Object Storage for the Healthcare Data Blues
The healthcare industry continues to face tremendous cost challenges. The U.S. government estimates national health expenditures in the United States accounted for $3.2 trillion last year – nearly 18% of the country’s total GDP. There are many factors that drive up the cost of healthcare, such as the cost of new drug development and hospital readmissions. In addition, there’s compelling studies that show medical organizations will need to evolve their IT environment to curb healthcare costs and improve patient care in new ways, such as cloud-based healthcare models aimed at research community collaboration, coordinated care and remote healthcare delivery.
For example, Goldman Sachs recently predicted that the digital revolution can save $300 billion in spending in the healthcare sector by powering new patient options, such as home-based patient monitoring and patient self-management. Moreover, the most significant progress may come from a medical organization transforming their healthcare data infrastructure. Here’s why:
- Advancements in digital medical imaging has resulted in an explosion of data that sits in picture archiving and communications systems (PACS) and vendor neutral archives (VNAs).
- Patient care initiatives such as personalized medicine and genomics require storing, sharing and analyzing massive amounts of unstructured data.
- Regulations such as the Health Insurance Portability and Accountability Act (HIPAA) require organizations to have policies for long term image retention and business continuity.
Unfortunately, traditional file storage approaches aren’t well-suited to manage vast amounts of unstructured data and present several barriers to modernizing healthcare infrastructure. A recent Taneja Group survey found the top three challenges to be:
- Lack of flexibility: Traditional file storage appliances require dedicated hardware and don’t offer tight integration with collaborative cloud storage environments.
- Poor utilization: Traditional file storage requires too much storage capacity for system fault tolerance, which reduces usable storage.
- Inability to scale: Traditional storage solutions such as RAID-based arrays are gated by controllers and simply aren’t designed to easily expand to petabyte storage levels.
As a result, healthcare organizations are moving to object storage solutions that offer an architecture inherently designed for web scale storage environments. Specifically, object storage offers healthcare organizations the following advantages:
- Simplified management, hardware independence and a choice of deployment options – private, public or hybrid cloud – lowers operational and hardware storage costs
- Web-scale storage platform provides scale as needed and enables a pay as you go model
- Efficient fault tolerance protects against site failures, node failures and multiple disk failures
- Built in security protects against digital and physical breeches
Public cloud customers have a range of storage options but still battle with complexity. IBM's Flex service is intended to ease that issue and get a leg up on the market.
- Premiered: 03/23/17
- Author: Taneja Group
- Published: TechTarget: Search Cloud Computing