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Trusted Business Advisors, Expert Technology Analysts

Research Areas

Data Center Systems

Includes HyperConverged, Converged, Disaggregated, and Legacy Infrastructure.

This category focuses on modern, on-premises infrastructure-based architectural approaches at the datacenter level. All aspects of the necessary infrastructure are included such as network, compute and storage. Taneja Group treats these systems as a complete solution for a particular workload whether it be general-purpose IaaS or vertical solutions targeted at specific use cases such as workload consolidation or applications such as SAP. We regularly compare and contrast the various architectural approaches that IT buyers are considering, evaluate their strengths and weaknesses, and discuss which approaches are likely to work best for specific workloads and use cases. We are always looking for shifts in industry thinking or technology adoption that might lead to an evolution of existing data center architectures, and engage with startup and large vendors alike to understand and characterize newly emerging approaches. Where possible, our reports and opinions are backed by primary research, including direct conversations with different classes of IT decision makers and influencers.

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Free Reports

Datrium’s Optimized Platform for Virtualized IT: “Open Convergence” Challenges HyperConvergence

The storage market is truly changing for the better with new storage architectures finally breaking the rusty chains long imposed on IT by traditional monolithic arrays. Vast increases in CPU power found in newer generations of servers (and supported by ever faster networks) have now freed key storage functionality to run wherever it can best serve applications. This freedom has led to the rise of all software-defined storage (SDS) solutions that power modular HyperConverged infrastructure (HCI). At the same time, increasingly affordable flash resources have enabled all-flash array options that promise both OPEX simplification and inherent performance gains. Now, we see a further evolution of storage that intelligently converges performance-oriented storage functions on each server while avoiding major problems with HyperConverged “single appliance” adoption.

Given the market demand for better, more efficient storage solutions, especially those capable of large scale, low latency and mixed use, we are seeing a new generation of vendors like Datrium emerge. Datrium studied the key benefits that hyperconvergence previously brought to market including the leverage of server-side flash for cost-effective IO performance, but wanted to avoid the all-in transition and the risky “monoculture” that can result from vendor-specific HCI. Their resulting design runs compute-intensive IO tasks scaled-out on each local application server (similar to parts of SDS), but persists and fully protects data on cost-efficient, persistent shared storage capacity. We have come to refer to this optimizing tiered design approach as “Server Powered Storage” (SPS), indicating that it can take advantage of the best of both shared and server-side resources.

Ultimately this results in an “Open Convergence” approach that helps virtualized IT environments transition off of aging storage arrays in an easier, flexible and more natural adoption path than with a fork-lift HyperConvergence migration. In this report we will briefly review the challenges and benefits of traditional convergence with SANs, the rise of SDS and HCI appliances, and now this newer “open convergence” SPS approach as pioneered by Datrium DVX. In particular, we’ll review how Datrium offers benefits ranging from elastic performance, greater efficiency (with independent scaling of performance vs. capacity), VM-centric management, enterprise scalability and mixed workload support while still delivering on enterprise requirements for data resiliency and availability.


DATA Challenges in Virtualized Environments

Virtualized environments present a number of unique challenges for user data. In physical server environments, islands of storage were mapped uniquely to server hosts. While at scale that becomes expensive, isolating resources and requiring a lot of configuration management (all reasons to virtualize servers), this at least provided directly mapped relationships to follow when troubleshooting, scaling capacity, handling IO growth or addressing performance.

However, in the virtual server environment, the layers of virtual abstraction that help pool and share real resources also obfuscate and “mix up” where IO actually originates or flows, making it difficult to understand who is doing what. Worse, the hypervisor platform aggregates IO from different workloads hindering optimization and preventing prioritization. Hypervisors also tend to dynamically move virtual machines around a cluster to load balance servers. Fundamentally, server virtualization makes it hard to meet application storage requirements with traditional storage approaches.

Current Virtualization Data Management Landscape

Let’s briefly review the three current trends in virtualization infrastructure used to ramp up data services to serve demanding and increasingly larger scale clusters:

  • Converged Infrastructure - with hybrid/All-Flash Arrays (AFA)
  • HyperConverged Infrastructure - with Software Defined Storage (SDS)
  • Open Converged Infrastructure - with Server Powered Storage (SPS)

Converged Infrastructure - Hybrid and All-Flash Storage Arrays (AFA)

We first note that converged infrastructure solutions simply pre-package and rack traditional arrays with traditional virtualization cluster hosts. The traditional SAN provides well-proven and trusted enterprise storage. The primary added value of converged solutions is in a faster time-to-deploy for a new cluster or application. However, ongoing storage challenges and pain points remain the same as in un-converged clusters (despite claims of converged management as these tend to just aggregate dashboards into a single view).

The traditional array provides shared storage from which virtual machines draw for both images and data, either across Fibre Channel or IP network (NAS or iSCSI). While many SAN’s in the hands of an experienced storage admin can be highly configurable, they do require specific expertise to administer. Almost every traditional array has by now become effectively hybrid, capable of hosting various amounts of flash, but if the array isn’t fully engineered for flash it is not going to be an optimal choice for an expensive flash investment. Hybrid arrays can offer good performance for the portion of IO that receives flash acceleration, but network latencies are far larger than most gains. Worse, it is impossible for a remote SAN to know which IO coming from a virtualized host should be cached/prioritized (in flash)– it all looks the same and is blended together by the time it hits the array.

Some organizations deploy even more costly all-flash arrays, which can guarantee array-side performance for all IO and promise to simplify administration overhead. For a single key workload, a dedicated AFA can deliver great performance. However, we note that virtual clusters mostly host mixed workloads, many of which don’t or won’t benefit from the expensive cost of persisting all data on all flash array storage. Bottomline - from a financial perspective, SAN flash is always more expensive than server-side flash. And by placing flash remote across a network in the SAN, there is always a relatively large network latency which denigrates the benefit of that array side flash investment.

HyperConverged Infrastructures - Software Defined Storage (SDS)

As faster resources like flash, especially added to servers directly, came down in price, so-called Software Defined Storage (SDS) options proliferated. Because CPU power has continuously grown faster and denser over the years, many traditional arrays came to be actually built on plain servers running custom storage operating systems. The resulting storage “software” often now is packaged as a more cost-effective “software-defined” solution that can be run or converged directly on servers (although we note most IT shops  prefer buying ready-to-run solutions, not software requiring on-site integration).

In most cases software-defined storage runs within virtual machines or containers such that storage services can be hosted on the same servers as compute workloads (e.g. VMware VSAN). An IO hungry application accessing local storage services can get excellent IO service (i.e. no network latency), but capacity planning and performance tuning in these co-hosted infrastructures can be exceedingly difficult. Acceptable solutions must provide tremendous insight or complex QoS facilities that can dynamically shift IO acceleration with workloads as they might move across a cluster (eg. to keep data access local).  Additionally, there is often a huge increase in East-West traffic between servers.

Software Defined Storage enabled a new kind of HyperConverged Infrastructure (HCI). Hyperconvergence vendors produce modular appliances in which a hypervisor (or container management), networking and (software-defined) storage all are pre-integrated to run within the same server. Because of vendor-specific storage, network, and compute integration, HCI solutions can offer uniquely optimized IO paths with plug-and-play scalability for certain types of workloads (e.g. VDI).

For highly virtualized IT shops, HCI simplifies many infrastructure admin responsibilities. But HCI presents new challenges too, not least among them is that migration to HCI requires a complete forklift turnover of all infrastructure. Converting all of your IT infrastructure to a unique vendor appliance creates a “full stack” single vendor lock-in issue (and increased risk due to lowered infrastructure “diversity”).

As server-side flash is cheaper than other flash deployment options, and servers themselves are commodity resources, HCI does help optimize the total return on infrastructure CAPEX – especially as compared to traditional silo’d server and SAN architectures. But because of the locked-down vendor appliance modularity, it can be difficult to scale storage independently from compute when needed (or even just storage performance from storage capacity). Obviously, pre-configured HCI vendor SKU’s also preclude using existing hardware or taking advantage of blade-type solutions.

With HCI, every node is also a storage node which at scale can have big impacts on software licensing (e.g. if you need to add nodes just for capacity, you will also pay for compute licenses), overbearing “East-West” network traffic, and in some cases unacceptable data availability risks (e.g. when servers lock/crash/reboot for any reason, an HCI replication/rebuild can be a highly vulnerable window).

OPEN Converged Infrastructure - Server Powered Storage (SPS)

When it comes to performance, IO still may need to transit a network incurring a latency penalty. To help, there are several third party vendors of IO caching that can be layered in the IO path – integrated with the server or hypervisor driver stack or even placed in the network. These caching solutions take advantage of server memory or flash to help accelerate IO. However, layering in yet another vendor and product into the IO path incurs additional cost, and also complicates the end-to-end IO visibility. Multiple layers of caches (vm, hypervisor, server, network, storage) can disguise a multitude of ultimately degrading performance issues.

Ideally, end-to-end IO, from within each local server to shared capacity, should all fall into a single converged storage solution – one that is focused on providing the best IO service by distributing and coordinating storage functionality where it best serves the IO consuming applications. It should also optimize IT’s governance, cost, and data protection requirements. Some HCI solutions might claim this in total, but only by converging everything into a single vendor appliance. But what if you want a easier solution capable of simply replace aging arrays in your existing virtualized environments – especially enabling scalability in multiple directions at different times and delivering extremely low latency while still supporting a complex mix of diverse workloads?

This is where we’d look to a Server Powered Storage (SPS) design. For example, Datrium DVX still protects data with cost-efficient shared data servers on the back-end for enterprise quality data protection, yet all the compute-intensive, performance-impacting functionality is “pushed” up into each server to provide local, accelerated IO. As Datrium’s design leverages each application server instead of requiring dedicated storage controllers, the cost of Datrium compared to traditional arrays is quite favorable, and the performance is even better than (and as scalable as) a 3rd party cache layered over a remote SAN.

In the resulting Datrium “open converged” infrastructure stack, all IO is deduped and compressed (and locally served) server-side to optimize storage resources and IO performance, while management of storage is fully VM-centric (no LUN’s to manage). In this distributed, open and unlocked architecture, performance scales with each server added to naturally scale storage performance with application growth.

Datrium DVX makes great leverage for a given flash investment by using any “bring-your-own” SSDs, far cheaper to add than array-side flash (and can be added to specific servers as needed/desired). In fact, most vm’s and workloads won’t ever read from the shared capacity on the network – it is write-optimized persistent data protection and can be filled with cost-effective high-capacity drives.

Taneja Group Opinion

As just one of IT’s major concerns, all data bits must be persisted and fully managed and protected somewhere at the end of the day. Traditional arrays, converged or not, just don’t perform well in highly virtualized environments, and using SDS (powering HCI solutions) to farm all that critical data across fungible compute servers invokes some serious data protection challenges. It just makes sense to look for a solution that leverages the best aspects of both enterprise arrays (for data protection) and software/hyperconverged solutions (that localize data services for performance).

At the big picture level, Server Powered Storage can be seen as similar (although more cost-effective and performant) to a multi-vendor solution in which IT layers server-side IO acceleration functionality from one vendor over legacy or existing SANs from another vendor. But now we are seeing a convergence (yes, this is an overused word these days, but accurate here) of those IO path layers into a single vendor product. Of course, a single vendor solution that fully integrates distributed capabilities in one deployable solution will perform better and be naturally easier to manage and support (and likely cheaper).

There is no point in writing storage RFP’s today that get tangled up in terms like SDS or HCI. Ultimately the right answer for any scenario is to do what is best for applications and application owners while meeting IT responsibilities. For existing virtualization environments, new approaches like Server Powered Storage and Open Convergence offer considerable benefit in terms of performance and cost (both OPEX and CAPEX). We highly recommend that before one invests in expensive all-flash arrays, or takes on a full migration to HCI, that an Open Convergence option like Datrium DVX be considered as a potentially simpler, more cost-effective, and immediately rewarding solution.


NOTICE: The information and product recommendations made by the TANEJA GROUP are based upon public information and sources and may also include personal opinions both of the TANEJA GROUP and others, all of which we believe to be accurate and reliable. However, as market conditions change and not within our control, the information and recommendations are made without warranty of any kind. All product names used and mentioned herein are the trademarks of their respective owners. The TANEJA GROUP, Inc. assumes no responsibility or liability for any damages whatsoever (including incidental, consequential or otherwise), caused by your use of, or reliance upon, the information and recommendations presented herein, nor for any inadvertent errors that may appear in this document.

Publish date: 11/23/16
Profile

Optimizing VM Storage Performance & Capacity - Tintri Customers Leverage New Predictive Analytics

Today we are seeing big impacts on storage from the huge increase in the scale of an organization’s important data (e.g. Big Data, Internet Of Things) and the growing size of virtualization clusters (e.g. never-ending VM’s, VDI, cloud-building). In addition, virtualization adoption tends to increase the generalization of IT admins. In particular, IT groups are focusing more on servicing users and applications and no longer want to be just managing infrastructure for infrastructure’s sake. Everything that IT does is becoming interpreted, analyzed, and managed in application/business terms, including storage to optimize the return on their total IT investment. To move forward, an organization’s storage infrastructure not only needs to grow internally smarter, it also needs to become both VM and application aware.

While server virtualization made a lot of things better for the over-taxed IT shop, delivering quality storage services in hypervisor infrastructures with traditional storage created difficult challenges. In response Tintri pioneered per-VM storage infrastructure. The Tintri VMstore has eliminated multiple points of storage friction and pain. In fact, it’s now becoming a mandatory checkbox across the storage market for all arrays to claim some kind of VM-centricity. Unfortunately, traditional arrays are mainly focused on checking off rudimentary support for external hypervisor APIs that only serve to re-package the same old storage. The best fit to today’s (and tomorrow’s) virtual storage requirements will only come from fully engineered VM-centric storage and application-aware approaches as Tintri has done.

However, it’s not enough to simply drop in storage that automatically drives best practice policies and handles today’s needs. We all know change is constant, and key to preparing for both growth and change is having a detailed, properly focused view of today’s large scale environments, along with smart planning tools that help IT both optimize current resources and make the best IT investment decisions going forward. To meet those larger needs, Tintri has rolled out a Tintri Analytics SaaS-based offering that applies big data analytical power to the large scale of their customer’s VMstore VM-aware metrics.

In this report we will look briefly at Tintri’s overall “per-VM” storage approach and then take a deeper look at their new Tintri Analytics offering. The new Tintri Analytics management service further optimizes their app-aware VM storage with advanced VM-centric performance and capacity management. With this new service, Tintri is helping their customers receive greater visibility, insight and analysis over large, cloud-scale virtual operations. We’ll see how “big data” enhanced intelligence provides significant value and differentiation, and get a glimpse of the payback that a predictive approach provides both the virtual admin and application owners. 

Publish date: 11/04/16
Free Reports

For Lowest TCO and Maximum Agility Choose the VMware Cloud Foundation Hybrid SDDC Platform

The race is on at full speed.  What race?  The race to bring public cloud agility and economics to a data center near you. Ever since the first integrated systems came onto the scene in 2010, vendors have been furiously engineering solutions to make on-premises infrastructure as cost effective and as easy to use as the public cloud, while also providing the security, availability, and control that enterprises demand. Fundamentally, two main architectures have evolved within the race to modernize data centers that will create a foundation enabling fully private and hybrid clouds. The first approach uses traditional compute, storage, and networking infrastructure components (traditional 3-tier) overlaid with varying degrees of virtualization and management software. The second more recent approach is to build a fully virtualized data center using industry standard servers and networking and then layer on top of that a full suite of software-based compute, network, and storage virtualization with management software. This approach is often termed a Software-Defined Data Center (SDDC).

The goal of an SDDC is to extend virtualization techniques across the entire data center to enable the abstraction, pooling, and automation of all data center resources. This would allow a business to dynamically reallocate any part of the infrastructure for various workload requirements without forklifting hardware or rewiring. VMware has taken SDDC to a new level with VMware Cloud Foundation.  VMware Cloud Foundation is the only unified SDDC platform for the hybrid cloud, which brings together VMware’s compute, storage, and network virtualization into a natively integrated stack that can be deployed on-premises or run as a service from the public cloud. It establishes a common cloud infrastructure foundation that gives customers a unified and consistent operational model across the private and public cloud.

VMware Cloud Foundation delivers an industry-leading SDDC cloud infrastructure by combining VMware’s highly scalable hyper-converged software (vSphere and VSAN) with the industry leading network virtualization platform, NSX. VMware Cloud Foundation comes with unique lifecycle management capabilities (SDDC Manager) that eliminate the overhead of system operations of the cloud infrastructure stack by automating day 0 to day 2 processes such as bring-up, configuration, workload provisioning, and patching/upgrades. As a result, customers can significantly shorten application time to market, boost cloud admin productivity, reduce risk, and lower TCO.  Customers consume VMware Cloud Foundation software in three ways: factory pre-loaded on integrated systems (VxRack 1000 SDDC); deployed on top qualified Ready Nodes from HPE, QCT, Fujitsu, and others in the future, with qualified networking; and run as a service from the public cloud through IBM, vCAN partners, vCloud Air, and more to come.

In this comparative study, Taneja Group performed an in-depth analysis of VMware Cloud Foundation deployed on qualified Ready Nodes and qualified networking versus several traditional 3-tier converged infrastructure (CI) integrated systems and traditional 3-tier do-it-yourself (DIY) systems. We analyzed the capabilities and contrasted key functional differences driven by the various architectural approaches. In addition, we evaluated the key CapEx and OpEx TCO cost components.  Taneja Group configured each traditional 3-tier system's hardware capacity to be as close as possible to the VMware Cloud Foundation qualified hardware capacity.  Further, since none of the 3-tier systems had a fully integrated SDDC software stack, Taneja Group added the missing SDDC software, making it as close as possible to the VMware Cloud Foundation software stack.  The quantitative comparative results from the traditional 3-tier DIY and CI systems were averaged together into one scenario because the hardware and software components are very similar. 

Our analysis concluded that both types of solutions are more than capable of handling a variety of virtualized workload requirements. However, VMware Cloud Foundation has demonstrated a new level of ease-of-use due to its modular scale-out architecture, native integration, and automatic lifecycle management, giving it a strong value proposition when building out modern next generation data centers.  The following are the five key attributes that stood out during the analysis:

  • Native Integration of the SDDC:  VMware Cloud Foundation natively integrates vSphere, Virtual SAN (VSAN), and NSX network virtualization.
  • Simplest operational experience: VMware SDDC Manager automates the life-cycle of the SDDC stack including bring up, configuration, workload provisioning, and patches/upgrades.
  •  
  • Isolated workload domains: VMware Cloud Foundation provides unique administrator tools to flexibly provision subsets of the infrastructure for multi-tenant isolation and security.
  • Modular linear scalability: VMware Cloud Foundation employs an architecture in which capacity can be scaled by the HCI node, by the rack, or by multiple racks. 
  • Seamless Hybrid Cloud: Deploy VMware Cloud Foundation for private cloud and consume on public clouds to create a seamless hybrid cloud with a consistent operational experience.

Taneja Group’s in-depth analysis indicates that VMware Cloud Foundation will enable enterprises to achieve significant cost savings. Hyper-converged infrastructure, used by many web-scale service providers, with natively integrated SDDC software significantly reduced server, storage, and networking costs.  This hardware cost saving more than offset the incremental SDDC software costs needed to deliver the storage and networking capability that typically is provided in hardware from best of breed traditional 3-tier components. In this study, we measured the upfront CapEx and 3 years of support costs for the hardware and software components needed to build out a VMware Cloud Foundation private cloud on qualified Ready Nodes.  In addition, Taneja Group validated a model that demonstrates the labor and time OpEx savings that can be achieved through the use of integrated end-to-end automatic lifecycle management in the VMware SDDC Manager software.

 

By investing in VMware Cloud Foundation, businesses can be assured that their data center infrastructure can be easily consumed, scaled, managed, upgraded and enhanced to provide the best private cloud at the lowest cost. Using a pre-engineered modular, scale-out approach to building at web-scale means infrastructure is added in hours, not days, and businesses can be assured that adding infrastructure scales linearly without complexity.  VMware Cloud Foundation is the only platform that provides a natively integrated unified SDDC platform for the hybrid cloud with end-to-end management and with the flexibility to provision a wide variety of workloads at the push of a button.

In summary, VMware Cloud Foundation enables at least five unparalleled capabilities, generates a 45% lower 3-year TCO than the alternative traditional 3-tier approaches, and delivers a tremendous value proposition when building out a modern hybrid SDDC platform. Before blindly going down the traditional infrastructure approach, companies should take a close look at VMware Cloud Foundation, a unified SDDC platform for the hybrid cloud.

Publish date: 10/17/16
Report

The Modern Data-Center: Why Nutanix Customers are Replacing Their NetApp Storage

Several Nutanix customers shared with Taneja Group why they switched from traditional NetApp storage to the hyperconverged Nutanix platform. Each customer talked about the value of hyperconvergence versus a traditional server/networking/storage stack, and the specific benefits of Nutanix in mission-critical production environments.

Hyperconverged systems are a popular alternative to traditional computing architectures that are built with separate compute, storage, and networking components. Nutanix turns this complex environment into an efficient, software-based infrastructure where hypervisor, compute, storage, networking, and data services run on scalable nodes that seamlessly scale across massive virtual environments.  

The customers we spoke with came from very different industries, but all of them faced major technology refreshes for legacy servers and NetApp storage. Each decided that hyperconvergence was the right answer, and each chose the Nutanix hyperconvergence platform for its major benefits including scalability, simplicity, value, performance, and support. The single key achievement running through all these benefits is “Ease of Everything”: ease of scaling, ease of management, ease of realizing value, ease of performance, and ease of upgrades and support. Nutanix simply works across small clusters and large, single and multiple datacenters, specialist or generalist IT, and different hypervisors.

The datacenter is not static. Huge data growth and increasing complexity are motivating IT directors from every industry to invest in scalable hyperconvergence. Given Nutanix benefits across the board, these directors can confidently adopt Nutanix to transform their data-centers, just as these NetApp customers did.

Publish date: 03/31/16
Report

The Hyperconverged Data Center: Nutanix Customers Explain Why They Replaced Their EMC SANS

Taneja Group spoke with several Nutanix customers in order to understand why they switched from EMC storage to the Nutanix platform. All of the respondent’s articulated key architectural benefits of hyperconvergence versus a traditional 3-tier solutions. In addition, specific Nutanix features for mission-critical production environments were often cited.

Hyperconverged systems have become a mainstream alternative to traditional 3-tier architecture consisting of separate compute, storage and networking products. Nutanix collapses this complex environment into software-based infrastructure optimized for virtual environments. Hypervisor, compute, storage, networking, and data services run on scalable nodes that seamlessly scale across massive virtual assets. Hyperconvergence offers a key value proposition over 3-tier architecture:  instead of deploying, managing and integrating separate components – storage, servers, networking, data services, and hypervisors – these components are combined into a modular high performance system.

The customers we interviewed operate in very different industries. In common, they all maintained data centers undergoing fundamental changes, typically involving an opportunity to refresh some portion of their 3-tier infrastructure. This enabled the evaluation of hyperconvergence in supporting those changes. Customers interviewed found that Nutanix hyperconvergence delivered benefits in the areas of scalability, simplicity, value, performance, and support. If we could use one phrase to explain why Nutanix’ is winning over EMC customers in the enterprise market it would be “Ease of Everything.” Nutanix works, and works consistently with small and large clusters, in single and multiple datacenters, with specialist or generalist IT support, and across hypervisors.

The five generations of Nutanix products span many years of product innovation. Web-scale architecture has been the key to Nutanix platform’s enterprise capable performance, simplicity and scalability. Building technology like this requires years of innovation and focus and is not an add-on for existing products and architectures.

The modern data center is quickly changing. Extreme data growth and complexity are driving data center directors toward innovative technology that will grow with them. Given the benefits of Nutanix web-scale architecture – and the Ease of Everything – data center directors can confidently adopt Nutanix as their partner in data center transformation just as the following EMC customers did.

Publish date: 03/31/16
Profile

Cohesity Data Platform: Hyperconverged Secondary Storage

Primary storage is often defined as storage hosting mission-critical applications with tight SLAs, requiring high performance.  Secondary storage is where everything else typically ends up and, unfortunately, data stored there tends to accumulate without much oversight.  Most of the improvements within the overall storage space, most recently driven by the move to hyperconverged infrastructure, have flowed into primary storage.  By shifting the focus from individual hardware components to commoditized, clustered and virtualized storage, hyperconvergence has provided a highly-available virtual platform to run applications on, which has allowed IT to shift their focus from managing individual hardware components and onto running business applications, increasing productivity and reducing costs. 

Companies adopting this new class of products certainly enjoyed the benefits, but were still nagged by a set of problems that it didn’t address in a complete fashion.  On the secondary storage side of things, they were still left dealing with too many separate use cases with their own point solutions.  This led to too many products to manage, too much duplication and too much waste.  In truth, many hyperconvergence vendors have done a reasonable job at addressing primary storage use cases, , on their platforms, but there’s still more to be done there and more secondary storage use cases to address.

Now, however, a new category of storage has emerged. Hyperconverged Secondary Storage brings the same sort of distributed, scale-out file system to secondary storage that hyperconvergence brought to primary storage.  But, given the disparate use cases that are embedded in secondary storage and the massive amount of data that resides there, it’s an equally big problem to solve and it had to go further than just abstracting and scaling the underlying physical storage devices.  True Hyperconverged Secondary Storage also integrates the key secondary storage workflows - Data Protection, DR, Analytics and Test/Dev - as well as providing global deduplication for overall file storage efficiency, file indexing and searching services for more efficient storage management and hooks into the cloud for efficient archiving. 

Cohesity has taken this challenge head-on.

Before delving into the Cohesity Data Platform, the subject of this profile and one of the pioneering offerings in this new category, we’ll take a quick look at the state of secondary storage today and note how current products haven’t completely addressed these existing secondary storage problems, creating an opening for new competitors to step in.

Publish date: 03/30/16
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