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The company’s storage virtualization software empowers organizations to seamlessly manage and scale their data storage architectures, delivering massive performance gains at a fraction of the cost of solutions offered by legacy storage hardware vendors. Backed by 10,000 customer sites around the world, DataCore’s adaptive and self-learning and healing technology takes the pain out of manual processes and helps deliver on the promise of the new software defined data center through its hardware agnostic architecture. \r\n\r\nDataCore clients represent the broad spectrum of IT organizations around the globe, spanning all the major vertical industries. Their physical infrastructures and environments consists of systems from all the major storage manufacturers, including Dell, EMC, Fujitsu-Siemens, Hitachi, HP, IBM, NetApp, and many others. \r\n\r\nDataCore storage virtualization software is sold through authorized distributors and integration partners across the world, many of which also specialize in server and desktop virtualization solutions.\r\n\r\nDataCore provides 24x7 post sales technical assistance through a highly talented customer service organization operating from key support centers in the U.S., U.K and Japan. \r\n\r\nSource: https://www.datacore.com/Company/about","companyTypes":["vendor"],"products":{},"vendoredProductsCount":1,"suppliedProductsCount":1,"supplierImplementations":[],"vendorImplementations":[],"userImplementations":[],"userImplementationsCount":0,"supplierImplementationsCount":0,"vendorImplementationsCount":0,"vendorPartnersCount":0,"supplierPartnersCount":0,"b4r":0,"categories":{"7":{"id":7,"title":"Storage - General-Purpose Disk Arrays","description":" General-purpose disk arrays refer to disk storage systems that work together with specialized array controllers to achieve high data transfer. They are designed to fulfill the requirement of a diverse set of workloads such as databases, virtual desktop infrastructure, and virtual networks. The market size in the study represents the revenue generated through various deployment modes such as NAS, SAN, and DAS. Some of the technologies used in the general-purpose disk arrays market include PATA, SATA, and SCSI. The application areas of general-purpose disk arrays include BFSI, IT, government, education &amp; research, healthcare, and manufacturing.\r\nGeneral-Purpose Disk Arrays market in BFSI accounts for the largest revenue. IT industry and governments are investing heavily in the general-purpose disk arrays, as a huge amount of voluminous data is getting generated which requires high storage capacity to store the classified data for analytics purpose and consumer insights. General-Purpose Disk Arrays market in healthcare is expected to show robust growth during the forecast period, as hospitals are adopting the latest technology with huge storage spaces in an attempt to track the patient history for providing better healthcare facilities.\r\nThe global general-purpose disk arrays market is fragmented owing to the presence of a large number of local and regional players, which intensifies the degree of rivalry. The market is growing at a notable pace, which leads to high intensity of rivalry. Key market players such as Dell EMC, HPE, and IBM Corporation seek to gain market share through continuous innovations in storage technology. Some of the other key players operating in a market are Hitachi, Seagate Technologies, NetApp, Promise Technologies, Quantum Corporation, Oracle Corporation, Fujitsu, DataDirect Networks, and Infortrend Technology Inc. Key competitors are specifically focusing on Asia-Pacific and Middle-East &amp; Africa regions, as they show strong tendency to adopt the general-purpose disk arrays in coming years.","materialsDescription":"<span style=\"font-weight: bold;\">What are the characteristics of storage?</span>\r\nStorage technologies at all levels of the storage hierarchy can be differentiated by evaluating certain core characteristics as well as measuring characteristics specific to a particular implementation. These core characteristics are volatility, mutability, accessibility, and addressability. For any particular implementation of any storage technology, the characteristics worth measuring are capacity and performance.\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Volatility</span></span>\r\nNon-volatile memory retains the stored information even if not constantly supplied with electric power. It is suitable for long-term storage of information. Volatile memory requires constant power to maintain the stored information. The fastest memory technologies are volatile ones, although that is not a universal rule. Since the primary storage is required to be very fast, it predominantly uses volatile memory.\r\nDynamic random-access memory is a form of volatile memory that also requires the stored information to be periodically reread and rewritten, or refreshed, otherwise it would vanish. Static random-access memory is a form of volatile memory similar to DRAM with the exception that it never needs to be refreshed as long as power is applied; it loses its content when the power supply is lost.\r\nAn uninterruptible power supply (UPS) can be used to give a computer a brief window of time to move information from primary volatile storage into non-volatile storage before the batteries are exhausted. Some systems, for example EMC Symmetrix, have integrated batteries that maintain volatile storage for several minutes.\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Mutability</span></span>\r\n<span style=\"font-weight: bold;\">Read/write storage or mutable storage</span>\r\n<div class=\"indent\">Allows information to be overwritten at any time. A computer without some amount of read/write storage for primary storage purposes would be useless for many tasks. Modern computers typically use read/write storage also for secondary storage.</div>\r\n<span style=\"font-weight: bold;\">Slow write, fast read storage</span>\r\n<div class=\"indent\">Read/write storage which allows information to be overwritten multiple times, but with the write operation being much slower than the read operation. Examples include CD-RW and SSD.</div>\r\n<span style=\"font-weight: bold;\">Write once storage</span>\r\n<div class=\"indent\">Write Once Read Many (WORM) allows the information to be written only once at some point after manufacture. Examples include semiconductor programmable read-only memory and CD-R.</div>\r\n<span style=\"font-weight: bold;\">Read only storage</span>\r\n<div class=\"indent\">Retains the information stored at the time of manufacture. Examples include mask ROM ICs and CD-ROM.</div>\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Accessibility</span></span>\r\n<span style=\"font-weight: bold;\">Random access</span>\r\n<div class=\"indent\">Any location in storage can be accessed at any moment in approximately the same amount of time. Such characteristic is well suited for primary and secondary storage. Most semiconductor memories and disk drives provide random access.</div>\r\n<span style=\"font-weight: bold;\">Sequential access</span>\r\n<div class=\"indent\">The accessing of pieces of information will be in a serial order, one after the other; therefore the time to access a particular piece of information depends upon which piece of information was last accessed. Such characteristic is typical of off-line storage.</div>\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Addressability</span></span>\r\n<span style=\"font-weight: bold;\">Location-addressable</span>\r\n<div class=\"indent\">Each individually accessible unit of information in storage is selected with its numerical memory address. In modern computers, location-addressable storage usually limits to primary storage, accessed internally by computer programs, since location-addressability is very efficient, but burdensome for humans.</div>\r\n<span style=\"font-weight: bold;\">File addressable</span>\r\n<div class=\"indent\">Information is divided into files of variable length, and a particular file is selected with human-readable directory and file names. The underlying device is still location-addressable, but the operating system of a computer provides the file system abstraction to make the operation more understandable. In modern computers, secondary, tertiary and off-line storage use file systems.</div>\r\n<span style=\"font-weight: bold;\">Content-addressable</span>\r\n<div class=\"indent\">Each individually accessible unit of information is selected based on the basis of (part of) the contents stored there. Content-addressable storage can be implemented using software (computer program) or hardware (computer device), with hardware being faster but more expensive option. Hardware content addressable memory is often used in a computer's CPU cache.</div>\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Capacity</span></span>\r\n<span style=\"font-weight: bold;\">Raw capacity</span>\r\n<div class=\"indent\">The total amount of stored information that a storage device or medium can hold. It is expressed as a quantity of bits or bytes (e.g. 10.4 megabytes).</div>\r\n<span style=\"font-weight: bold;\">Memory storage density</span>\r\n<div class=\"indent\">The compactness of stored information. It is the storage capacity of a medium divided with a unit of length, area or volume (e.g. 1.2 megabytes per square inch).</div>\r\n\r\n<span style=\"font-weight: bold;\"><span style=\"font-style: italic;\">Performance</span></span>\r\n<span style=\"font-weight: bold;\">Latency</span>\r\n<div class=\"indent\">The time it takes to access a particular location in storage. The relevant unit of measurement is typically nanosecond for primary storage, millisecond for secondary storage, and second for tertiary storage. It may make sense to separate read latency and write latency (especially for non-volatile memory[8]) and in case of sequential access storage, minimum, maximum and average latency.</div>\r\n<span style=\"font-weight: bold;\">Throughput</span>\r\n<div class=\"indent\">The rate at which information can be read from or written to the storage. In computer data storage, throughput is usually expressed in terms of megabytes per second (MB/s), though bit rate may also be used. As with latency, read rate and write rate may need to be differentiated. Also accessing media sequentially, as opposed to randomly, typically yields maximum throughput.</div>\r\n<span style=\"font-weight: bold;\">Granularity</span>\r\n<div class=\"indent\">The size of the largest &quot;chunk&quot; of data that can be efficiently accessed as a single unit, e.g. without introducing additional latency.</div>\r\n<span style=\"font-weight: bold;\">Reliability</span>\r\n<div class=\"indent\">The probability of spontaneous bit value change under various conditions, or overall failure rate.</div>\r\nUtilities such as hdparm and sar can be used to measure IO performance in Linux.\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Energy use</span></span>\r\n<ul><li>Storage devices that reduce fan usage, automatically shut-down during inactivity, and low power hard drives can reduce energy consumption by 90 percent.</li><li>2.5-inch hard disk drives often consume less power than larger ones. Low capacity solid-state drives have no moving parts and consume less power than hard disks. Also, memory may use more power than hard disks. Large caches, which are used to avoid hitting the memory wall, may also consume a large amount of power.</li></ul>\r\n\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Security</span></span>\r\nFull disk encryption, volume and virtual disk encryption, andor file/folder encryption is readily available for most storage devices.\r\nHardware memory encryption is available in Intel Architecture, supporting Total Memory Encryption (TME) and page granular memory encryption with multiple keys (MKTME) and in SPARC M7 generation since October 2015.","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_Storage_General_Purpose_Disk_Arrays.png","alias":"storage-general-purpose-disk-arrays"},"27":{"id":27,"title":"ODMS - Operational Database Management System","description":"Operational database management systems (also referred to as OLTP On-Line Transaction Processing databases) are used to update data in real-time. These types of databases allow users to do more than simply view archived data. Operational databases allow you to modify that data (add, change or delete data), doing it in real-time. OLTP databases provide transactions as the main abstraction to guarantee data consistency that guarantees the so-called ACID properties. Basically, the consistency of the data is guaranteed in the case of failures and/or concurrent access to the data.\r\nSince the early 90s, the operational database software market has been largely taken over by SQL engines. Today, the operational DBMS market (formerly OLTP) is evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases. NoSQL databases typically have focused on scalability and have renounced to data consistency by not providing transactions as OLTP systems do. Operational databases are increasingly supporting distributed database architecture that can leverage distribution to provide high availability and fault tolerance through replication and scale-out ability.\r\nThe growing role of operational databases in the IT industry is moving fast from legacy databases to real-time operational databases capable to handle distributed web and mobile demand and to address Big data challenges. Recognizing this, Gartner started to publish the Magic Quadrant for Operational Database Management Systems in October 2013.\r\nOperational databases are used to store, manage and track real-time business information. For example, a company might have an operational database used to track warehouse/stock quantities. As customers order products from an online web store, an operational database can be used to keep track of how many items have been sold and when the company will need to reorder stock. An operational database stores information about the activities of an organization, for example, customer relationship management transactions or financial operations, in a computer database.\r\nOperational databases allow a business to enter, gather, and retrieve large quantities of specific information, such as company legal data, financial data, call data records, personal employee information, sales data, customer data, data on assets and much other information. An important feature of storing information in an operational database is the ability to share information across the company and over the Internet. Operational databases can be used to manage mission-critical business data, to monitor activities, to audit suspicious transactions, or to review the history of dealings with a particular customer. They can also be part of the actual process of making and fulfilling a purchase, for example in e-commerce.","materialsDescription":" <span style=\"font-weight: bold;\">What is DBMS used for?</span>\r\nDBMS, commonly known as Database Management System, is an application system whose main purpose revolves around the data. This is a system that allows its users to store the data, define it, retrieve it and update the information about the data inside the database.\r\n<span style=\"font-weight: bold;\">What is meant by a Database?</span>\r\nIn simple terms, Database is a collection of data in some organized way to facilitate its user’s to easily access, manage and upload the data.\r\n<span style=\"font-weight: bold;\">Why is the use of DBMS recommended? Explain by listing some of its major advantages.</span>\r\nSome of the major advantages of DBMS are as follows:\r\n<ul><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Controlled Redundancy:</span></span> DBMS supports a mechanism to control the redundancy of data inside the database by integrating all the data into a single database and as data is stored at only one place, the duplicity of data does not happen.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Data Sharing:</span></span> Sharing of data among multiple users simultaneously can also be done in DBMS as the same database will be shared among all the users and by different application programs.</li><li> Backup and Recovery Facility: DBMS minimizes the pain of creating the backup of data again and again by providing a feature of ‘backup and recovery’ which automatically creates the data backup and restores the data whenever required.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Enforcement of Integrity Constraints:</span></span> Integrity Constraints are very important to be enforced on the data so that the refined data after putting some constraints are stored in the database and this is followed by DBMS.</li><li><span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">Independence of Data:</span></span> It simply means that you can change the structure of the data without affecting the structure of any of the application programs.</li></ul>\r\n<span style=\"font-weight: bold;\">What is the purpose of normalization in DBMS?</span>\r\nNormalization is the process of analyzing the relational schemas which are based on their respective functional dependencies and the primary keys in order to fulfill certain properties.\r\n<span style=\"font-style: italic;\"><span style=\"font-weight: bold;\">The properties include:</span></span>\r\n<ul><li>To minimize the redundancy of the Data.</li><li>To minimize the Insert, Delete and Update Anomalies.</li></ul>","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_ODMS.png","alias":"odms-operational-database-management-system"}},"branches":"Information Technology","companySizes":"101 to 500 Employees","companyUrl":"https://www.datacore.com/","countryCodes":[],"certifications":[],"isSeller":true,"isSupplier":false,"isVendor":true,"presenterCodeLng":"","seo":{"title":"DataCore Software","keywords":"storage, DataCore, through, software, virtualization, data, customer, many","description":"DataCore Software is a leader in software-defined storage. 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The company’s storage virtualization software empowers organizations to seamlessly manage and scale their data storage architectures, delivering massive performance gains at a fraction of the cost of s","og:image":"https://old.roi4cio.com/uploads/roi/company/DataCore_Software.png"},"eventUrl":"","vendorPartners":[],"supplierPartners":[],"vendoredProducts":[{"id":291,"logoURL":"https://old.roi4cio.com/fileadmin/user_upload/SANsymphony_TM_.png","logo":true,"scheme":false,"title":"SANsymphony™","vendorVerified":0,"rating":"1.00","implementationsCount":0,"suppliersCount":0,"supplierPartnersCount":0,"alias":"sansymphonytm","companyTitle":"DataCore Software","companyTypes":["vendor"],"companyId":2806,"companyAlias":"datacore-software","description":"The SANsymphony software runs on standard x86 servers, providing one set of common storage services across all storage devices under its control.\r\nThe combined storage capacity of the different devices is managed as shared pools to eliminate wasted space.\r\nUnlike storage systems communicate seamlessly reducing complexity and preventing downtime.\r\nData is replicated between nodes leaving \u000bno single point of failure.\r\nYou can seamlessly scale up and scale out choosing the most appropriate hardware manufacturer for each class of storage and servers.\r\nSANsymphony™ Software-defined Storage platform solves difficult storage-related challenges introduced by server and desktop virtualization, cloud computing and more general expansion, business continuity, and disaster recovery initiatives. It creates an active, transparent virtualization layer across disk storage devices to maximize the availability, performance and utilization of datacenters large and small. &nbsp;The integrated set of centrally-managed data protection (CDP), provisioning, caching, replication, and migration functions operates uniformly over different models and brands, assimilating current and future equipment non-disruptively. &nbsp;You will find that SANsymphony software cost-effectively speeds up applications, delivers uninterrupted data access and extends the life of your tiered storage investments, while giving you peace of mind.","shortDescription":"SANsymphony™ software, powered by DataCore™ Parallel I/O technology, is storage virtualization solution. In use at over 10,000+ customer sites, it maximizes IT infrastructure performance, availability and utilization by virtualizing storage hardware","type":null,"isRoiCalculatorAvaliable":false,"isConfiguratorAvaliable":false,"bonus":100,"usingCount":2,"sellingCount":4,"discontinued":0,"rebateForPoc":0,"rebate":0,"seo":{"title":"SANsymphony™","keywords":"storage, devices, scale, seamlessly, different, SANsymphony™, across, software","description":"The SANsymphony software runs on standard x86 servers, providing one set of common storage services across all storage devices under its control.\r\nThe combined storage capacity of the different devices is managed as shared pools to eliminate wasted space.\r\nUnl","og:title":"SANsymphony™","og:description":"The SANsymphony software runs on standard x86 servers, providing one set of common storage services across all storage devices under its control.\r\nThe combined storage capacity of the different devices is managed as shared pools to eliminate wasted space.\r\nUnl","og:image":"https://old.roi4cio.com/fileadmin/user_upload/SANsymphony_TM_.png"},"eventUrl":"","translationId":292,"dealDetails":null,"roi":null,"price":null,"bonusForReference":null,"templateData":[],"testingArea":"","categories":[{"id":383,"title":"Software-defined storage platforms, SDS","alias":"software-defined-storage-platforms-sds","description":" <span style=\"font-weight: bold;\">Software-defined storage (SDS)</span> is a marketing term for computer data storage software for policy-based provisioning and management of data storage independent of the underlying hardware. \r\n<span style=\"font-weight: bold;\">SDS software</span> typically includes a form of storage virtualization to separate the storage hardware from the software that manages it. The software enabling a software-defined storage environment may also provide policy management for features such as data deduplication, replication, thin provisioning, snapshots and backup.<br /><br /><span style=\"font-weight: bold;\">SDS system</span> hardware may or may not also have abstraction, pooling, or automation software of its own. When implemented as software only in conjunction with commodity servers with internal disks, it may suggest software such as a virtual or global file system. If it is software layered over sophisticated large storage arrays, it suggests software such as storage virtualization or storage resource management, categories of products that address separate and different problems. If the policy and management functions also include a form of artificial intelligence to automate protection and recovery, it can be considered as intelligent abstraction.\r\n<span style=\"font-weight: bold;\">Software-defined storage solutions</span> may be implemented via appliances over a traditional storage area network (SAN), or implemented as network-attached storage (NAS), or using object-based storage. ","materialsDescription":"<h1 class=\"align-center\"> <span style=\"font-weight: normal;\">What does SDS mean?</span></h1>\r\n<span style=\"font-weight: bold; \">SDS </span>stays for <span style=\"font-weight: bold; \">software-defined storage </span>solution - it is a computer program that manages data storage resources and functionality and has no dependencies on the underlying physical storage hardware.\r\nAll storage systems have always been software-defined. What's changed is that the <span style=\"font-weight: bold; \">software has become portable</span>.\r\nBut nothing in the storage world elicits more divergent opinions than the term &quot;software-defined storage products&quot;. With no universally accepted definition, SDS is vendor-specific. Software defined storage leaders shape the SDS definition to match their storage offerings. The result is that every storage vendor appears to offer SDS.\r\nStorage system software historically was tied to the hardware it managed. When the hardware ran out of capacity or performance, it had to be replaced and the software licensing was repurchased along with the hardware.<br />What made matters significantly worse was that storage system architectures created isolated silos. Unique infrastructures made everything from storage provisioning, data protection, disaster recovery, tech refresh, data migration, power and cooling more and more untenable. Compound that with the ongoing trend of rapid data growth and the need to store ever-increasing amounts of data, and the available architectures made storage systems management too complicated, difficult, expensive and ultimately unmaintainable.\r\n<h1 class=\"align-center\"><span style=\"font-weight: normal;\">What are SDS categories pros and cons?</span></h1>\r\n&nbsp;With no working standard SDS definition, a variety of technologies have emerged in the software-defined storage market. For our purposes, the four categories of SDS include: \r\n<ul><li class=\"align-left\"><span style=\"font-weight: bold; \">Hypervisor-based SDS</span></li><li class=\"align-left\"><span style=\"font-weight: bold; \">Hyper-converged infrastructure (HCI) SDS</span></li><li class=\"align-left\"><span style=\"font-weight: bold; \">Storage virtualization SDS</span></li><li class=\"align-left\"><span style=\"font-weight: bold; \">Scale-out object and/or file SDS</span></li></ul>\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">&nbsp;Hypervisor-based SDS pros:</span><br /> </p>\r\n<span style=\"font-weight: bold; \">Flexibility</span>. VSAN works with both hard disk drives (HDDs) and solid-state drives (SSDs), including DIMM-based flash drives, PCIe, SAS, SATA and even NVMe. VMware vSAN supports both HDDs and SSDs in a hybrid mode or all SSDs in all-flash mode.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Scalability and performance</span>. VSAN is highly scalable while delivering high levels of performance. It scales out through vSphere clustering and can support up to 64 vSphere hosts per cluster. Each vSphere host supports approximately 140 TB raw storage capacity and well north of 8 PB of raw storage capacity per cluster. On the performance side, each vSAN host can supply 100,000 or more IOPS, yielding millions of IOPS per cluster.\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Hypervisor-based SDS cons:</span></p>\r\n<span style=\"font-weight: bold; \">Scalability and performance issues.</span> If a VM requires more IOPS than one physical vSphere host can provide, it can get them from other nodes in the cluster, but with a considerable latency penalty. Inter-cluster storage performance is another issue. Most vSAN clusters use 10 Gbps to 40 Gbps Ethernet and TCP/IP to interconnect the hosts. This architecture essentially replaces a deterministic system bus with a non-deterministic TCP/IP network so latencies between hosts become highly variable. Unless the cluster uses more sophisticated and faster interconnections, its storage performance from one clustered host to another will be highly variable and inconsistent.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Some things are not so simple. </span>Converting from a siloed storage environment to a pure vSAN requires converting non-VM images to VMs first. It's a time-consuming process for non-vSphere environments.\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Hyper-converged infrastructure (HCI) SDS pros:</span></p>\r\n<span style=\"font-weight: bold; \">Scalability and performance.</span> Scaling HCI is as simple as adding a node to the cluster. Scaling storage capacity just requires adding drives (HDDs or SSDs) up to a node's maximum or adding additional nodes. Each HCI product has its own scalability and performance limitations; however, most scale well into the PBs and add performance linearly with each server node added to the cluster.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Simplicity. </span>Plug it in, turn it on, configure and you're done. Few systems are simpler. No DIY, and there's just one throat to choke for support.\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Hyper-converged infrastructure (HCI) SDS cons:</span></p>\r\n<span style=\"font-weight: bold; \">Scalability and performance issues.</span> HCI cluster capacity is limited by the number of nodes supported in the cluster and the amount of capacity supported per node. If a VM requires more IOPS than a given host can provide, it can get IOPS from other nodes, but with a considerable latency penalty. Inter-cluster storage performance is another issue. Most HCI clusters use 10 Gbps to 40 Gbps Ethernet and TCP/IP to interconnect the hosts so latencies between hosts can be highly variable.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Some things are not so simple.</span> Converting from a siloed storage environment to an HCI cluster requires first converting both non-VM images and VMs to the HCI VMs or Docker containers, a time-consuming process.\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Storage virtualization SDS pros:</span></p>\r\n<span style=\"font-weight: bold; \"></span><span style=\"font-weight: bold;\">Flexibility.</span> It works with most x86 physical hosts or VMs as long as the hardware or hypervisor is certified and supported by the vendor. It converts all storage that sits behind it into the virtual storage pool, enabling repurposing of older storage. The scale-out versions permit physical or VM access to any node. Multi-copy mirroring isn't necessary to protect against a single controller failure, although it's available. Storage virtualization SDS can be provided as software or bundled with server hardware similar to HCI.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Total cost of ownership (TCO)</span>. The biggest cost savings in storage virtualization SDS comes from commodity hardware and server-based drives. Another cost saving comes from inline data reduction technologies. Compared to equivalent storage systems, most storage virtualization SDS will yield a much more favorable TCO.<span style=\"font-weight: bold; \"><br /></span>\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Storage virtualization SDS cons:</span></p>\r\n<span style=\"font-weight: bold;\">Flexibility issues. </span>Most storage virtualization SDS can only run on the specific commodity hardware certified and supported by the vendor. Products that can run as VSAs require hypervisors certified and supported by the vendor.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Scalability and performance issues.</span> On paper, these systems support tremendous capacity scalability, but the pragmatic approach is a bit different. Storage virtualization SDS capacity is constrained by x86 server limitations. Each server can handle only so much capacity before performance declines below acceptable levels. Storage virtualization SDS scale-out is constrained by clustering because the number of storage controller nodes supported is limited. Performance may also be constrained by the same limitations. \r\n<p class=\"align-center\"><span style=\"font-weight: bold; \">Scale-out object and/or file SDS pros:<br /></span></p>\r\n<span style=\"font-weight: bold; \">Scalability and performance. </span>Scaling is multi-dimensional: each node can be scaled individually and generally the cluster itself can add nodes for capacity or performance. Performance for both will never approach that of high-performance block storage.<span style=\"font-weight: bold; \"></span><span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Simplicity. </span>When bundled with hardware, scale-out object or file storage is very simple to set up, configure, and manage. Implementing it as software requires DIY systems integration. Both types leverage commodity hardware, have exceptional scalability and -- in the case of scale-out object storage -- unmatched data resilience and longevity via erasure coding.\r\n<p class=\"align-center\"><span style=\"font-weight: bold;\">Scale-out object and/or file SDS cons:</span></p>\r\n<span style=\"font-weight: bold;\">Flexibility issues. </span>Whether delivered as software or bundled with hardware, the hardware must be certified and supported by the vendors.\r\n<span style=\"font-weight: bold; \">Scalability and performance issues.</span> Scale-out file SDS generally doesn't scale as high as scale-out object storage, but object will have somewhat higher latencies. Object storage has significant additional latencies from the metadata and data resiliency functions. Both types are best suited for secondary applications where high performance is not a requirement.<span style=\"font-weight: bold; \"></span>\r\n<span style=\"font-weight: bold; \">Some things are not so simple. </span>When scale-out file or object storage SDS is purchased as software, it's a DIY project, so special skills, professional services or a systems integrator may be required.\r\n\r\n","iconURL":"https://old.roi4cio.com/fileadmin/user_upload/icon_Software_defined_storage_platforms.png"}],"characteristics":[],"concurentProducts":[],"jobRoles":[],"organizationalFeatures":[],"complementaryCategories":[],"solutions":[],"materials":[],"useCases":[],"best_practices":[],"values":[],"implementations":[]}],"suppliedProducts":[],"partnershipProgramme":{"levels":[{"id":569,"level":"AGGREGATORS"},{"id":571,"level":"CLOUD SERVICE PROVIDERS"},{"id":573,"level":"PROFESSIONAL SERVICE PROVIDERS"},{"id":575,"level":"SYSTEM BUILDERS"},{"id":577,"level":"Distributor"}],"partnerDiscounts":{"AGGREGATORS":"","CLOUD SERVICE PROVIDERS":"","PROFESSIONAL SERVICE PROVIDERS":"","SYSTEM BUILDERS":"","Distributor":""},"registeredDiscounts":{"AGGREGATORS":"","CLOUD SERVICE PROVIDERS":"","PROFESSIONAL SERVICE PROVIDERS":"","SYSTEM BUILDERS":"","Distributor":""},"additionalBenefits":[],"salesPlan":{"AGGREGATORS":"","CLOUD SERVICE PROVIDERS":"","PROFESSIONAL SERVICE PROVIDERS":"","SYSTEM BUILDERS":"","Distributor":""},"additionalRequirements":[]}}},"aliases":{},"links":{},"meta":{},"loading":false,"error":null},"implementations":{"implementationsByAlias":{},"aliases":{},"links":{},"meta":{},"loading":false,"error":null},"agreements":{"agreementById":{},"ids":{},"links":{},"meta":{},"loading":false,"error":null},"comparison":{"loading":false,"error":false,"templatesById":{},"comparisonByTemplateId":{},"products":[],"selectedTemplateId":null},"presentation":{"type":null,"company":{},"products":[],"partners":[],"formData":{},"dataLoading":false,"dataError":false,"loading":false,"error":false},"catalogsGlobal":{"subMenuItemTitle":""}}