In this report, Eric Burgener, Research Vice President at IDC provides an overview of key Big Memory market dynamics. He proposes that as real-time analytics workloads become more prevalent, the gap in the memory/storage hierarchy is highlighting a significant market opportunity that is addressed by Big Memory Computing. Eric talks about a confluence of market and technology enablers, definitions of big memory technologies, the benefits of Big Memory, and key early use cases for Big Memory Computing. Read this report if you want a 3600 view of Big Memory in 10 minutes.

1. IDC TECHNOLOGY SPOTLIGHT
Sponsoredby:MemVerge
Big Memory Computing Emerges to Better
Enable Data-Intensive IT
June 2020
Written by: Eric Burgener, Research Vice President, Infrastructure Systems, Platforms, and Technologies Group
Introduction
Digitaltransformation (DX)—theevolutionamongenterprisesofallsizes
towardmuchmoredata-drivenbusinessmodels—isunderwayinmost
industries.Moredatathaneverbeforeisbeingcaptured,stored,
protected,andanalyzed,and ITorganizationsare morefocusedthanever
ondrivingdirectbusinessvaluefromthedatatheycollecton customers,
productsandservices,markets,andinternalprocessesandworkflows.
Next-generationapplications(NGAs)arebeingdeployedtohelpdrivethis
value,andmanyofthememploya"bigdataanalytics"orientationthat
leveragesdata-intensivetechnologiessuchasartificialintelligence (AI),
machinelearning (ML),anddeeplearningtogleaninsightsthatresultin
betterbusinessdecisions.Real-timeworkloadsareappearinginmany
industries—examplesincludefraud analyticsinfinancialservices,
customerprofilinginsocialmediaand streaming, InternetofThings(IoT)
applications,andsecurityandcyberthreatdetectionacrossmanydifferent
industries—andthepercentageofreal-timedataisontherise.
Thesetypesofreal-timebigdataanalyticsworkloadsareputtingperformancedemandsonITinfrastructurethatarevery
difficulttomeet costeffectivelywithlegacyarchitectures.Butperformance isnottheonlychallenge.Asenterprises
evolvetheirbusinessmodels,manyoftheseNGAsformthefoundationforcompetitivedifferentiation,andtheyare
increasinglybeingviewedasmissioncritical.Indeed,IDCpredictsthatby2021,60–70%ofthe Global2000willhaveat
leastone real-timebigdataanalyticsworkloadthatisalso considered missioncritical.AsenterprisesmodernizetheirIT
infrastructuretomeetthese evolvingperformance and availabilityrequirements,the largeperformancegapinthe
memory/storagehierarchybetween volatile,byte-addressable,andexpensivemain memoryandblock-addressable
solid statedisks(SSDs)(which arebothpersistent and lessexpensiveona$/GBbasis)isbecomingincreasingly
problematic.Althoughsome applicationshavebeenwrittento run inmainmemory(e.g.,OracleDatabaseIn-Memory,
SAPHANA)toimprovetheperformanceandefficiencyof resourceutilization,today'smainmemorycapacityisstillquite
limited. Inaddition,thecatalogofofferingsthathavebeenrewritteninthismannerisextremelylimitedbecause itisa
major software engineeringprojecttoretoolanapplicationforin-memoryoperation.
As real-time analytics workloads become more prevalent, the gap in the memory/storage
hierarchy is highlighting a significant market opportunity that is addressed by a new market
category called Big Memory Computing.
KEY TAKEAWAYS
» Many new workloads being deployed by
enterprises undergoing digital
transformation demand memory-class
performance.
» By combining Persistent Memory
technology with software-defined
memory virtualization, Big Memory
Computing meets new workflow needs.
» Because Big Memory Computing runs on
industry-standard server hardware and
does not require any application
modifications, enterprises should be able
to easily evaluate how the technology can
apply to them.
AT A GLANCE

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IDC TECHNOLOGY SPOTLIGHT Big Memory Computing Emerges to Better Enable Data-Intensive IT
Asreal-time,mission-criticalbigdataanalyticsworkloadsbecomemoreprevalent,this"gap"inthememory/storage
hierarchyishighlightingasignificantmarketopportunity. Whatisneeded isanabilitytosignificantlyextendthe capacity
ofmainmemorytoaccommodatemuch largerdatasetswitha solution exhibitingnear-DRAMperformanceatlower
costthatisbothpersistentand appropriateformission-criticalworkloads.Tomaximizenear-termadoption,thissolution
shoulddeliverthesecapabilitieswithoutrequiringexistingapplicationstobe rewritten.
A Confluence of Market and Technology Enablers
Thepreviouslydefinedsolutionshouldcome asnosurprisetoITpractitioners,butuntilrecently,themarket imperative
andthetechnologytosolvetheproblemdidnotexist.Atthebeginningofthepastdecade,severalsmallstart-ups
attemptedtoaddressthisissue,buta strongmarketrequirementandthekeytechnologiesneededto solveitwerenot
there.Thesituation isverydifferenttoday.WiththerecentexplosioninAI/ML-drivenreal-timebigdataanalytics,the
marketneedforaviablenear-term solution isclear,directlyrelatedtobusinesssuccessformanyenterprises,andwill
becomewidespreadoverthenext12–24months.
Unlikeadecadeago,severalnewtechnologieshavearisenthatmakeitpracticaltoaddressthisneedtoday.Thefirstis
the concentratedcomputepower,nowwidespread,that'sneededtoleveragetechnologiessuchasAI/MLforbigdata
analytics.MulticoreCPUsandgeneral-purpose GPUsareavailableinvolumefrommultiplevendors,affordablydelivering
themassive computepower neededforreal-timeAI/ML-drivenworkloads.
Thesecondisanewclassofstorage,referredto asPersistentMemory(PM),that ispersistent,byteaddressable,
availableinmuchlargercapacitiesthantraditionalDRAMDIMMs,costslessona$/GBbasisthanDRAM,anddelivers
accesslatenciesintheseveralhundrednanosecondrange.PMproductsareavailabletodayfromasinglevendorbutare
expectedtobeavailableinvolumefrommultiplevendorsby2022.IDCexpectsthatfrom2019to2023,thePM market
willgrowata248%compoundannualgrowthrate (CAGR)tocrest$2.6billioninannualrevenue.
Thethirdtechnologyisasoftware-definedmemoryvirtualizationlayerthat createsalogicalpoolofpersistentstorage
composedofbothDRAMandPMthat canbe sharedacrossserversthrougha switched remotedirectmemoryaccess
(RDMA)network.Thisisnot anNVMeoverFabricsnetwork(which supportsblock-addressabletraffic);thisisan RDMA
networkthat supportsbyte-addressabletraffic. This"memorylake"willprovide significantlyhighercapacitiesthanDRAM
technologyaloneatablendedcost/GBthatisalreadylowerthanthatofDRAMandwillcontinuetodropasmultiple
vendorsbeginto shipproductsin volume.
TomeetNGArequirements,thismemoryvirtualizationlayershouldincludeseveralkeyfeaturesbesidesjust memory
pooling. First,itshouldprovideintelligentdataplacementwithinthememorylaketo optimizeaccesslatenciesand
generalperformance.Second,itshouldincludeenterprise-classdataservicesthatenable mission-criticaloperation.
Ataminimum,thisshouldincludedataprotectionfeaturessuchasRAIDand/orerasure codingandfastrecovery
featuressuchassnapshotsand replication.Giventhattradingandfinancialmarketanalyticsare anearlyusecase,
encryptionwouldalsobean attractive earlyfeature.Third,itshouldbeusablewithexistingworkloadswithoutrequiring
anyapplicationrewrites.

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Definitions
IDCbelievesthatthepreviouslymentioned marketopportunityandsolutiondefinitionwillbecomethebasisfor anew
market category.An aptnameforthismarketthat isbothdescriptive and shortisBigMemoryComputing. The solution
outlinedpreviouslyrequirestechnologiesfromatleastseveralvendors,anditisimportanttonotethatmultiplevendors
arealreadyworkingonboththehardware componentsandthesoftwarecomponentsforthisplatform. Figure 1
providesasimple,nonvendor-specificdefinitionofBigMemoryComputing.
FIGURE 1: The DefinitionofBig Memory Computing
Source: IDC, 2020
Benefits
Thebusinessbenefitsof BigMemoryComputingareclear.First,itputsmoredatacloserto computeresourcesand
makesthedataaccessibleatDRAM-like speeds,providingsignificantlymore consistentandscalableperformancethan is
possiblewithtoday'smemory/storagehierarchy. Bigdataanalyticsworkloadsthatrequirehighdegreesofconcurrency
whileworkingonverylargedatasetswillbe abletodrivebetterresultsfasterwiththisnewparadigm. Infact,manyof
thesenewworkloadswouldnotevenbefeasiblewithoutthecombinationofacceleratedcomputeand BigMemory
Computing.Asdata setsgrowandreal-timeapplicationsbecomemorepervasive,BigMemoryComputingwillbecomea
requiredpartofthe ITinfrastructureformoreenterprises.
Second,the software-definedmemoryvirtualizationlayerunlocksthetruepotentialofthenewPMhardware.Muchlike
the server virtualization (hypervisor)layerenabledtheparallelismtotakefulladvantageofmulticoreCPUarchitectures,
thememoryvirtualizationtierwilldothesameforthenewPMmedia.Thiswilldrive improvedefficienciesintermsof
increased ITinfrastructureandmixedenterpriseworkloaddensity,streamliningdatacentersbyloweringenergyand
floorspaceconsumptioncosts.Withsupportforenterprise-classdataservicessuchasRAID,snapshots,andreplicationfor
memory-residentdatabuiltintothismemoryvirtualizationtier,ITmanagershavethetoolstoprovidethehighavailability
andfastrecoveryneededformission-criticalworkloads.Inaddition,theabilitytocreateamemorylakethatsignificantly

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IDC TECHNOLOGY SPOTLIGHT Big Memory Computing Emerges to Better Enable Data-Intensive IT
transcendsthememorycapacityofanysingle serverandenablessharingacrossmanyserversaddressestoday'sDRAM
capacitylimitations.Ultimately,BigMemoryComputingshouldsupportmemorylakeshundredsofterabytesin size,
deliveringthehighconcurrencynecessaryevenasthescaleof"bigdata"growsovertime.
Third,theintroductionofamemorylakewillstreamlineinfrastructure,allowingsmallerconfigurationstomeetanygiven
performancegoal.FormanyofthetargetNGAworkloads,theintroductionofBigMemoryComputingwilltranscendthe
needforolder-stylepersistent"performancestorage,"allowingthattiertoberemovedentirely.Themuchloweraverage
latenciesdrivenbytheBigMemorytier(relativetotheolderperformancestorage)willdrivehigherCPUutilization,allowing
customerstogetmoreoutofcomputeresources.ThisimprovedefficiencycantranslatetofewerCPUcores(andultimately
servers)neededtomeetagivenperformancelevel,whichinturncandrivelowerapplicationsoftwarelicensingcosts.
TheabilitytodelivertheadvantagesofBigMemoryComputingfortoday'sworkloadswithoutrequiringanyapplication
modificationswillbecriticaltothesuccessofthisnewcategory.Givingenterprisestheabilitytoaccesstheperformance
advantagesofthisnewapproachquicklyandeasilywillbe keytorapidadoption.Thevisionof BigMemoryComputingis
thatcustomerscanuseindustry-standard servers,runningwidelyavailableLinuxoperatingsystems,addPMhardware
and memoryvirtualization software,andthen immediatelyenjoytheperformancebenefitsofin-memorycomputing.
Despitetheclearperformanceadvantagesofin-memorycomputing,wehavealreadyseenthatwhen applicationsmust
bespecificallymodifiedtotake advantageofitandmain memorycapacityremainslimited,adoptionproceedsvery
slowly. Sotheabilitytoquicklyandeasilyadopt in-memorycomputingforexistingworkloadswithoutmodificationwith
largememorylakeswillbecriticaltorapidmarketpenetration.
Considering MemVerge
Foundedin2017andheadquarteredinMilpitas,California,MemVergeisastoragesoftwarecompanythatprovidesthe
memoryvirtualizationlayerforBigMemoryComputing.Thevendor'sBigMemoryComputingvisionhasgarneredthesupport
ofmanykeyindustryplayersthathavebecomeinvestors,includingIntel,Cisco,NetApp,andSKhynix.MemVerge'sMemory
Machinesoftwareinstallsonindustry-standardIntelArchitectureserversrunningLinux,allofwhichareinterconnectedusing
anInfiniBandRDMAnetwork.DRAMandPMcapacityfromallattachedserversarepooledintoamemorylakeaccessibleby
allservers.TheMemoryMachineincludesenterprise-classdataservicessuchasZeroIOSnapshot,RDMA-basedreplication,
andmemorytiering,givingadministratorsthetoolsneededtorunmission-criticalworkloadsinMemoryMachine
environments.Anyoftoday'sworkloadscanberuninthisenvironmentwithoutrequiringanymodifications,enabling
applicationstoquicklyandeasilybenefitfromtheperformanceandefficiencyofin-memoryoperation.
MemVerge'simplementation,whileprovidingbackward compatibilitywithexistingapplications,offersseveral APIs.
WithTransparentMemoryService,theMemoryMachineusescombinedDRAMandPMcapacityasvolatilememory,
extendingmainmemorycapacitywhilemakingitoverallmoreaffordable(duetotheblended$/GBcostofDRAMand
PM). Inthat case,theoperatingsystem just seestheadditionalPMcapacityasmore mainmemory. In addition,
MemVergedeliversanin-memorysnapshotfeature,utilizingthepersistenceoftheunderlyingmemory,ontopofthe
TransparentMemoryService.Suchsnapshotsare instantandnondisruptivetoapplications,enablingapplicationrollback,
crashrecovery,and cloning.MemVergeMemoryMachinealsoincludesaSoftwareDevelopmentKit (SDK)with APIs,and
if ITorganizationswanttomodifyorbuildapplicationsusingtheSDK,theycan getmoregranularcontrolofthe memory
virtualizationlayerforimprovedefficiencyofoperation,havemorecomplete accesstodataservices,andpossiblyenjoy
moreperformance(dependingonaworkload'sI/Oprofileandworkflows).

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IDC TECHNOLOGY SPOTLIGHT Big Memory Computing Emerges to Better Enable Data-Intensive IT
MemVergeistargetingseveralusecaseswithitsBigMemoryComputingplatform(seeFigure2).Thefirstusecaseisinreal-
timedataanalyticsandordermanagementwherelowerlatenciestranslatedirectlytoimprovedrevenuestreams.
Tradingfloorapplicationsandotherworkloadsthathavesingle-threadedsequencerscanbenefitsignificantlyfromthe
muchlowerlatenciesofBigMemoryComputing(whichcanbeinthe200–400nanosecondrange).Thesecondusecaseis
forin-memorydatabasecloning.MemVerge'spatentedZeroIOSnapshotenablesscalableclonecreationwithout
noticeablelatencyimpactswhenthesamedatasetneedstobeusedfordifferentworkflows(suchasdev/test,analytics,or
reporting),whilethepersistentbutsharedmemorypoolsupportsalmostinstantaneousrecoveryintheeventofserveror
applicationcrashes.ThethirdusecaseisinAI/ML-assistedworkloadssuchasfrauddetectionorinferenceengineswhere
theperformancecandropdramaticallywhentherelevantdatasetislargerthanthemainmemorycapacity.Theabilityto
recoverrapidlyusingMemVerge'ssnapshottechnologyisasignificantadvantageinthisusecaseaswell.
FIGURE 2: Key Early UseCases forBig Memory Computing
Source: IDC, 2020
MemVergeisbenefitingfrom someverylargeandwell-knownnamesinenterprise computinginitsgo-to-market
strategy.KeyinvestorsincludeCisco,Intel,NetApp,andSKhynixaswellasseveralventurecapitalists.Cisco isa major
servervendorlookingtodifferentiatefromitscompetitorsbybeingfirsttomarketwithconverged infrastructure
offeringsthatsupportBigMemoryComputing. IntelisafirstmoverinthePMhardware arena,NetAppalreadyoffersa
PMsolutionforitsONTAP-basedenterprise storagearrays,andSKhynixisamarketleaderinsolidstatememory
technologies.MemVerge'scurrent go-to-marketapproachisbasedaround a100%indirectchannelstrategy,butthe
companywillbenefitsignificantlyfromthemarketpowerofthese vendorsastheyestablish marketbeachheadsthatwill
introduce BigMemoryComputingtotheenterpriseinfrastructure.
IntelwasthefirstvendortointroducegenerallyavailablePMproducts(whichthevendorbrandsunderthe IntelOptane
Data CenterPersistentMemoryname).Optaneproductsuseanewmediatypethatthevendorjointlydevelopedwith
Microncalled3DXPoint,andultimatelyMicronisexpectedtoshipPMproductsinvolumeaswell. Intelusesthe3D
XPointmediainbothbyte-addressable (PM)andblock-addressable (storage-classmemoryorSCM)storagedevices,
whichthevendorisalreadysellingtoday. IntelOptaneData CenterPersistentMemoryproductsplugdirectlyinto
standardmemoryslotsonIntelArchitecture systemsandareaccessibleusingthebyte-addressableDDR4interface.

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IDC TECHNOLOGY SPOTLIGHT Big Memory Computing Emerges to Better Enable Data-Intensive IT
Today, BigMemoryComputingspecificallyusesIntel'sPMproducts (whichhavebuilt-inencryptionfordata atrest),but
the vendor'sOptaneSSDs(whilesignificantlylessperformantthan Intel'sPMproducts)arethefastestblock-addressable
storagedevicesavailableonthemarkettoday. IntelOptaneData CenterPersistentMemorydeliversroughlyanorderof
magnitudelowerlatenciesthan Optane SSDs.GivenIntel'smarketleadershippositioninPMproductstoday,itmakes
perfectsensethatthecompanywouldbeoneoftheearlyinvestorsinMemVerge.
Challenges
Despitetheclearmarketneedforandappealof BigMemoryComputing,thisisanewmarketthatwillrequire
evangelicalworktogenerate awareness.ThefactthatMemVerge'spartnerecosystemincludesmajorplayers suchas
Cisco,Intel,NetApp,andSKhynixwillhelp amplifyMemVerge'smessageevenasthe vendorprovidesthecredibilityto
encourageITorganizationstoseriouslyconsideritasanear-term solution.MemVerge'sdecisiontosupporta
compatibilitymodewasa verysmartonebecause itmakesitrelativelyeasyforprospectivebuyerstotryitout and
validatethebenefits.ThePMhardwarenecessaryforthissolution isalsorelativelynew (thefirstIntelOptaneData
CenterPersistentMemoryproductsshippedincalendar2Q19)andstillpricedabithigherthanitwillbeoncethe
technologyisshippinginvolumefrom multiplevendors. Still,evenatthisearlystage,there areclearusecaseswhere
BigMemoryComputingmakescompetitive andeconomicsense.
Conclusion
WithMemVerge'srecentMemoryMachineannouncement,wehaveenteredthe eraof
BigMemoryComputing.Burgeoningrequirementsinreal-timebigdataanalyticsdrivea
strongmarketneed,whilea confluenceofotherhardware and softwaretechnologies
thatonlyrecentlybecameavailablemakethisaviableplatformformission-critical
computingtoday.BigMemoryComputingpromisestounlockthetrueperformance
potentialofthenewPersistentMemorytechnology,enablingthe creationof
cost-effectivemainstream computingplatformsfor manyoftheNGAsthatfuel
competitivedifferentiationfordigitallytransformedenterprises.IDChasdefinedthe
BigMemoryComputingcategoryinthispaperandexpectsthatwithintwo yearsthere
willbea vibrantmultivendor communityofferingthesetypesofplatforms.
Today,MemVergeistheplayerthat isalreadyofferingthesesolutions.Cofounder
CharlesFan(whowasthegeneralmanagerofVMware'svSANbusiness)haspulledtogetheracompellingecosystemof
bellwetherpartnerstofuelMemVerge'sgo-to-marketefforts,andthatecosystemisexpectedtodrivemarquee end
userstoseriouslyevaluateBigMemoryComputingastheplatformofchoiceformission-criticalreal-timeanalytics
workloads.IDCbelievesthat BigMemoryComputingaddressesanimportant marketneed,thatthenecessary
technologyenablersareinplace,andthatenterpriseswithreal-timebigdataanalyticsandotherin-memorytype
workloadsshouldtakeaseriouslookatMemVerge'sMemoryMachineplatform.Thenecessaryhardwareproducts
and memoryvirtualizationfeaturesaretheretoday,andenterpriseslookingformemory-classperformancefor
mission-criticalworkloadsshouldtakenote.
Big Memory
Computing
promises to
unlock the true
performance
potential of the new
Persistent Memory
technology.

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About the Analyst
EricBurgener,Research Vice President, Infrastructure Systems, Platforms, and
Technologies
EricBurgenerisResearchVicePresidentwithinIDC'sEnterpriseInfrastructurepractice.Mr.Burgener'score
researchcoverageincludesstoragesystems,softwareandsolutions,quarterlytrackers,andend-user
researchaswellasadvisoryservicesandconsultingprograms.Basedonhisbackgroundcoveringenterprise
storage,Mr.Burgener'sresearchincludesaparticularemphasisonsolidstatetechnologiesinenterprise
storagesystemsaswellassoftware-definedinfrastructure.HewasawardedtheAlexanderMotsenigos
MemorialAwardforOutstandingInnovationinMarketResearchin2017byIDC,wasrecognizedasoneof
theArchitectAnalystPower100in2019byindependentresearcherARInsights,andisanactiveparticipant
intheITBuyer'sResearchProgramatIDC.
The content in this paper was adapted from existing IDC research published on www.idc.com.
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