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
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
If you are an existing customer of HPE 3PAR, this latest release of 3PAR capabilities will leave you smiling. If you are looking for an All Flash Array (AFA) to transform your data center, now might be the time to take a closer at HPE 3PAR. Since AFAs first emerged on the scene at the turn of this decade, the products have gone through various waves of innovation to achieve the market acceptance it has today. In the first wave, it was all about raw performance for niche applications. In the second wave, it was about making flash more cost effective versus traditional disk-based arrays to broaden economic appeal. Now in the final wave, it is about giving these arrays all the enterprise features and ecosystem support to completely replace all legacy Tier 0/1 arrays still in production today.
HPE 3PAR StoreServ is one of the leading AFAs on the market today. HPE 3PAR uses a modern architectural design that includes multi-controller scalability, a highly-virtualized data layer with three levels of abstraction, system-wide striping, a highly-specialized ASIC and numerous flash innovations. HPE 3PAR engineers pioneered this very efficient architecture well before flash technology became mainstream and proved that this architecture approach has been timeless by demonstrating a seamless transition to support all-flash technology. During this same time, other vendors ran into architectural controller-bound bottlenecks for flash, making them reinvent existing products or completely start from scratch with new architectures.
HPE’s 3PAR timeless architecture has meant that features introduced years before are still relevant today and features introduced today are available to current 3PAR customers that purchased arrays previously. This continuous innovation of features available to old and new customers alike provides the ultimate in investment protection unmatched by most vendors in the industry today. In this Technology Brief, Taneja Group will explore some of the latest developments from HPE that build upon the rich feature set that already exists in the 3PAR architecture. These new features and simplicity enhancements will show that HPE continues to put customer’s investment protection first and continues to expand its capabilities around enterprise-grade business continuity and resilience. The combination of economic value of HPE 3PAR AFAs with years of proven mission critical features promises to accelerate the final wave of the much-anticipated All-Flash Data Center for Tier 0/1 workloads.
These days the world operates in real-time all the time. Whether making airline reservations or getting the best deal from an online retailer, data is expected to be up to date with the best information at your fingertips. Businesses are expected to meet this requirement, whether they sell products or services. Having this real-time, actionable information can dictate whether a business survives or dies. In-memory databases have become popular in these environments. The world's 24X7 real-time demands cannot wait for legacy ERP and CRM application rewrites. Companies such as SAP devised ways to integrate disparate databases by building a single super-fast uber-database that could operate with legacy infrastructure while simultaneously creating a new environment where real-time analytics and applications can flourish. These capabilities enable businesses to succeed in the modern age, giving forward-thinking companies a real edge in innovation.
SAP HANA is an example of an application environment that uses in-memory database technology and allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows HANA to process data stored in RAM as opposed to reading it from a disk. At the heart of SAP HANA is a database that operates on both
OLAP and OLTP database workloads simultaneously. SAP HANA can be deployed on-premises or in the cloud. Originally, on-premises HANA was available only as a dedicated appliance. Recently SAP has expanded support to best in class components through their SAP Tailored Datacenter Integration (TDI) program. In this solution profile, Taneja Group examined the storage requirements needed for HANA TDI environments and evaluated storage alternatives including the HPE 3PAR StoreServ All Flash. We will make a strong case as to why all-flash arrays like the HPE 3PAR version are a great fit for SAP HANA solutions.
Why discuss storage for an in-memory database? The reason is simple: RAM loses its mind when the power goes off. This volatility means that persistent shared storage is at the heart of the HANA architecture for scalability, disaster tolerance, and data protection. The performance attributes of your shared storage dictate how many nodes you can cluster into a SAP HANA environment which in turn affects your business outcomes. Greater scalability capability means more real-time information is processed. SAP HANA workload shared storage requirements are write intensive with low latency for small files and sequential throughput performance for large files. However, the overall storage capacity is not extreme which makes this workload an ideal fit for all-flash arrays that can meet performance requirements with the smallest quantity of SSDs. Typically you would need 10X the equivalent spinning media drives just to meet the performance requirements, which then leaves you with a massive amount of capacity that cannot be used for other purposes.
In this study, we examined five leading all-flash arrays including the HPE 3PAR StoreServ 8450 All Flash. We found that the unique architecture of the 3PAR array could meet HANA workload requirements with up to 73% fewer SSDs, 76% less power, and 60% less rack space than the alternative AFAs we evaluated.