Digital Transformation Driving New “Big Memory” Requirements

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For the first time, a major industry analyst defines the new category called Big Memory. Eric Burgener, Research Vice President at IDC, describes the drivers for Big Memory, a forecast for byte-addressable Persistent Memory revenue, and a concise definition of the Big Memory category.

Software

Digital Transformation Driving New “Big Memory” Requirements
Eric Burgener, Research Vice President
Infrastructure Systems, Platforms and Technologies Group
May 2020
© IDC

© IDC 2
What Is Digital Transformation (DX)?
The digitization of
business models,
processes, products and
services
Sets enterprises up to
optimally take advantage
of big data analytics

© IDC 3
91.1% of enterprises undergoing DX
in the next three years
More data-centric business models
will drive AI/ML-infused analytics
Performance and availability
implications for enterprise storage
Market evolution will drive demand
for persistent memory technologies
Digital Transformation is Widespread
DX Maturity Distribution

© IDC 4
35
30
25
20
15
10
5
0
Worldwide, data is
growing at a 26.0%
CAGR, and in 2024
there will be 143
zettabytes of data
created
By 2021, 60-70% of the
Global 2000 will have at
least one mission-
critical real-time
workload
Real-Time Workloads Are On The Rise

© IDC 5
PM Revenue Forecast, 2019 - 2023
$0.00
$500.00
$1,000.00
$1,500.00
$2,000.00
$2,500.00
$3,000.00
Revneue ($M)
2019 2020 2021 2022 2023
REVENUE($M) $2609M248% CAGR
2019-2023
$65M

© IDC 6
CONFLUENCE OF
AVAILABLE TECHNOLOGIES
▪ Artificial intelligence and machine learning
▪ More concentrated compute power than ever before
▪ Emerging persistent memory technologies
▪ Memory virtualization with intelligent data placement
MARKET EVOLUTION
TO REAL-TIME
▪ Upping the ante: massive data sets, real-time orientation
▪ For accelerated computing, storage is still the bottleneck
▪ Value propositions include competitive differentiation, increased revenue
Business Drivers
TARGET
WORKLOADS
▪ Latency-sensitive transactional workloads (trading floor apps, etc.)
▪ Real-time big data analytics in financial services, healthcare, retail, etc.
▪ AI/ML analytics and inferencing (fraud analytics, social media, etc.)

© IDC 7
Defining “Big Memory Computing”
▪ Enables the ability to run applications in memory
for improved performance and efficiency
▪ Leverages byte addressable memory media
▪ Includes enterprise-class data services to handle
tier 1 availability and management requirements
▪ Runs on a software-based memory virtualization
layer on industry standard hardware without
application modification
▪ The technology enabler for mission-critical real-
time computingCAPACITY STORAGE
BIG MEMORY
(DRAM, PM)
COMPUTE
CAPACITY STORAGE
MEMORY
COMPUTE
PERFORMANCE
STORAGE
OLD MODEL BIG MEMORY
COMPUTING

Thank You!
© IDC
Eric Burgener
Research VP, Infrastructure Systems, Platforms and Technologies Group
eburgener@idc.com

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Digital Transformation Driving New “Big Memory” Requirements

1. Digital Transformation Driving New “Big Memory” Requirements Eric Burgener, Research Vice President Infrastructure Systems, Platforms and Technologies Group May 2020 © IDC

2. © IDC 2 What Is Digital Transformation (DX)? The digitization of business models, processes, products and services Sets enterprises up to optimally take advantage of big data analytics

3. © IDC 3 91.1% of enterprises undergoing DX in the next three years More data-centric business models will drive AI/ML-infused analytics Performance and availability implications for enterprise storage Market evolution will drive demand for persistent memory technologies Digital Transformation is Widespread DX Maturity Distribution

4. © IDC 4 35 30 25 20 15 10 5 0 Worldwide, data is growing at a 26.0% CAGR, and in 2024 there will be 143 zettabytes of data created By 2021, 60-70% of the Global 2000 will have at least one mission- critical real-time workload Real-Time Workloads Are On The Rise

5. © IDC 5 PM Revenue Forecast, 2019 - 2023 $0.00 $500.00 $1,000.00 $1,500.00 $2,000.00 $2,500.00 $3,000.00 Revneue ($M) 2019 2020 2021 2022 2023 REVENUE($M) $2609M248% CAGR 2019-2023 $65M

6. © IDC 6 CONFLUENCE OF AVAILABLE TECHNOLOGIES ▪ Artificial intelligence and machine learning ▪ More concentrated compute power than ever before ▪ Emerging persistent memory technologies ▪ Memory virtualization with intelligent data placement MARKET EVOLUTION TO REAL-TIME ▪ Upping the ante: massive data sets, real-time orientation ▪ For accelerated computing, storage is still the bottleneck ▪ Value propositions include competitive differentiation, increased revenue Business Drivers TARGET WORKLOADS ▪ Latency-sensitive transactional workloads (trading floor apps, etc.) ▪ Real-time big data analytics in financial services, healthcare, retail, etc. ▪ AI/ML analytics and inferencing (fraud analytics, social media, etc.)

7. © IDC 7 Defining “Big Memory Computing” ▪ Enables the ability to run applications in memory for improved performance and efficiency ▪ Leverages byte addressable memory media ▪ Includes enterprise-class data services to handle tier 1 availability and management requirements ▪ Runs on a software-based memory virtualization layer on industry standard hardware without application modification ▪ The technology enabler for mission-critical real- time computingCAPACITY STORAGE BIG MEMORY (DRAM, PM) COMPUTE CAPACITY STORAGE MEMORY COMPUTE PERFORMANCE STORAGE OLD MODEL BIG MEMORY COMPUTING

8. Thank You! © IDC Eric Burgener Research VP, Infrastructure Systems, Platforms and Technologies Group eburgener@idc.com

Digital Transformation Driving New “Big Memory” Requirements

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Digital Transformation Driving New “Big Memory” Requirements