SlideShare a Scribd company logo
© 2015 Hazelcast Inc.
It’s Time to Make the Move to In-Memory
Data Grids

Featuring Greg Luck, Forrester Research’s Mike Gualtieri, and 

Ellie Mae’s Ken Kolda
© 2015 Hazelcast Inc.
Featuring
2
GREG LUCK
CEO,
HAZELCAST
MIKE GUALTIERI
PRINCIPAL
ANALYST,
FORRESTER
RESEARCH
KEN KOLDA
SOFTWARE
ARCHITECT,
ELLIE MAE
Make The Move To In-Memory Data
Grids
Mike Gualtieri, Principal Analyst
July 16, 2015
Twitter: @mgualtieri
Planning, implementing, or expanding the use of
in-memory data platform.
73%
Base: 1,805 global data and analytics decision-makers
Source: Forrester Global Business Technographics Data And Analytics Online Survey, 2015
#Priority
© 2015 Forrester Research, Inc. Reproduction Prohibited 6
52%
53%
53%
54%
58%
64%
64%
65%
66%
73%
75%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Better leverage big data and analytics in business decision-
Create a comprehensive strategy for addressing digital
Create a comprehensive digital marketing strategy
Better comply with regulations and requirements
Improve differentiation in the market
Increase influence and brand reach in the market
Address rising customer expectations
Improve our ability to innovate
Reduce costs
Improve our products /services
Improve the experience of our customers
Customer experience is a top business priority
over the next 12 months
Base: 3,005 global data and analytics decision-makers
Source: Global Business Technographics Data And Analytics Online Survey, 2015
For you For all For segments For you
CRM
Hyper-Personal,
Real-Time Digital
Experiences
Personal
Relationships
Mass
Production
CustomerExperience
1800 1900 1950 2000 2015
#Celebrity
Customers want and increasingly expect
to be treated like celebrities.
•  Use analytics to learn
customer characteristics
and behavior
•  Detect real-time context
•  Adapt applications to serve
an individual customer
Celebrity experiences must:
Be Blazing Fast
#In-Memory
Ubiquitous, near-zero latency for even the most
complex data and compute operations.
DEFINITION
FORRESTERTechnologies that are principally architected to
use chip-based memory to accelerate the
performance of data access and applications;
and reduce the complexity of app development.
Scale should not limit design decisions.
110010011011001
010010011011001
010011001101101
010010011011001
Historical
Transactions
Customerdata
Security
The performance vagaries of accessing data
silos can be eliminated.
Fault-tolerance is non-negotiable.
Confidential information must be secure.
In-memory must fit and work seamlessly with
existing architectures.
In-Memory technology speeds application
development by reducing architectural concerns.
#Priority
73%
#Opportunity
What if you had
ubiquitous, near-zero
latency for even the most
complex data and
compute operations?
#DataGrids
© 2015 Forrester Research, Inc. Reproduction Prohibited 25
G GG
S S S
Streaming
Analytics
B B B
General-purpose data
processing cluster
D
Scale-up
Database
Data And
Compute Grid
DDD
Clustered
Database
#UseCases
Overcome legacy architectural bottlenecks
such as databases.
Real-time integration for shared cache.
Fast distributed processing.
forrester.com
Thank you
Mike Gualtieri
mgualtieri@forrester.com
Twitter: @mgualtieri
HAZELCAST  @  ELLIE  MAE
Ken  Kolda
SOFTWARE  ARCHITECT
About  Ellie  Mae
•  Founded  in  1997  to  provide  soDware  soluFons  to  mortgage  
industry
•  Released  Encompass  loan  originaFon  system  in  2003
•  Boxed,  on-­‐premise  soDware  sold  in  retail  stores
•  Target  market  was  2  –  20  user  mortgage  broker
•  Started  offering  Hosted  model  in  2007
•  Relieved  customers  from  burden  of  IT  infrastructure,  processes
•  Roughly  80%  of  customers  currently  use  Hosted  model,  with  customers  up  
to  3000  users
•  Began  engineering  of  “Next  Gen”  soluFon  in  2013
•  Hybrid  cloud  model  for  truly  SaaS  soluFon
7/22/15
©2015  Ellie  Mae.  All  rights  reserved.  
 32
7/22/15
©2015  Ellie  Mae.  All  rights  reserved.  
 33
The  Problem  of  Scale
•  Legacy  Architecture
•  .NET-­‐based  client/server  applicaFon  with  
SQL  Server  back-­‐end
•  Designed  for  on-­‐premise,  single-­‐tenant  
deployment
•  Scalability  Limits
•  Server  adapted  to  support  limited  mulF-­‐
tenancy
•  Home-­‐grown,  in-­‐process  caching  added  
to  ease  load  on  SQL  Server
•  Cache  synchronizaFon  issues  prevent  
horizontal  scale,  load  balancing
Data
Store
Encompass	
  Clients
Write Read
Encompass	
  
Server
Cache
Encompass	
  
Server
Cache
Encompass	
  
Server
Cache
Data
Store
Encompass	
  Clients
Write Read
Encompass	
  
Server
Encompass	
  
Server
Encompass	
  Clients
Write Read
Data
Store
7/22/15
©2015  Ellie  Mae.  All  rights  reserved.  
 34
Horizontal  Scale  via  Hazelcast
•  Distributed  Cache  Tier
•  In-­‐process  cache  replaced  with  
shared  Hazelcast  data  grid
•  Hazelcast  locking  used  to  ensure  
transacFonal  consistency  between  
server  nodes
•  Scalability  &  Availability
•  App  Fer  can  now  scale  horizontally
•  EliminaFon  of  single  point  of  failure
•  App  servers  can  be  brought  up/
down  without  loss  of  cache
•  Hazelcast  cluster  can  be  expanded  
to  meet  future  demands

Encompass	
  
Server
Encompass	
  
Server
Encompass	
  Clients
Write Read
Data
Store
7/22/15
©2015  Ellie  Mae.  All  rights  reserved.  
 35
Choosing  Hazelcast
•  Requirements/Use  cases
•  Database  caching:  Cross-­‐process  locks,  Hibernate  second-­‐level  caching
•  Session  storage:  TTL  and  Idle  Time  support,  evicFon/expiraFon  noFficaFons  
&  policies
•  NaFve  support  for  .NET,  Java  clients;  REST  support
•  High-­‐performance,  highly  available,  horizontally  scalable
•  Enterprise  support
•  EvaluaFon  process
•  High-­‐level  evaluaFon  of  8  in-­‐memory  data  grids  (JDG,  Couchbase,  JvCache,  
Terracona,  Riak,  Redis,  Memcached)
•  Six-­‐month  PoC  on  top  three  contenders  (Hazelcast,  JDG,  JvCache)
•  Rated  on  criteria  including  performance,  fault  tolerance,  client  support,  
ease-­‐of-­‐configuraFon/operaFon,  monitoring,  noFficaFons
7/22/15
©2015  Ellie  Mae.  All  rights  reserved.  
 36
EvaluaFon  Results
*	
  Note:	
  Evalua-on	
  performed	
  using	
  Hazelcast	
  3.0	
  
Thank  You!
Time to Make the Move to In-Memory Data Grids

More Related Content

What's hot

Oracle Coherence: in-memory datagrid
Oracle Coherence: in-memory datagridOracle Coherence: in-memory datagrid
Oracle Coherence: in-memory datagrid
Emiliano Pecis
 
In memory grids IMDG
In memory grids IMDGIn memory grids IMDG
In memory grids IMDG
Prateek Jain
 
Hazelcast for Terracotta Users
Hazelcast for Terracotta UsersHazelcast for Terracotta Users
Hazelcast for Terracotta Users
Hazelcast
 
5 Advantages of EDB's RemoteDBA Services
5 Advantages of EDB's RemoteDBA Services5 Advantages of EDB's RemoteDBA Services
5 Advantages of EDB's RemoteDBA Services
EDB
 
In Memory Data Grids, Demystified!
In Memory Data Grids, Demystified! In Memory Data Grids, Demystified!
In Memory Data Grids, Demystified!
Uri Cohen
 
Oracle Coherence
Oracle CoherenceOracle Coherence
Oracle Coherence
Liran Zelkha
 
Oracle Coherence
Oracle CoherenceOracle Coherence
Oracle Coherence
Mustafa Ahmed
 
Best Practices & Lessons Learned from Deployment of PostgreSQL
 Best Practices & Lessons Learned from Deployment of PostgreSQL Best Practices & Lessons Learned from Deployment of PostgreSQL
Best Practices & Lessons Learned from Deployment of PostgreSQL
EDB
 
Migration DB2 to EDB - Project Experience
 Migration DB2 to EDB - Project Experience Migration DB2 to EDB - Project Experience
Migration DB2 to EDB - Project Experience
EDB
 
Best practices: running high-performance databases on Kubernetes
Best practices: running high-performance databases on KubernetesBest practices: running high-performance databases on Kubernetes
Best practices: running high-performance databases on Kubernetes
MariaDB plc
 
Active/Active Database Solutions with Log Based Replication in xDB 6.0
Active/Active Database Solutions with Log Based Replication in xDB 6.0Active/Active Database Solutions with Log Based Replication in xDB 6.0
Active/Active Database Solutions with Log Based Replication in xDB 6.0
EDB
 
Oracle big data appliance and solutions
Oracle big data appliance and solutionsOracle big data appliance and solutions
Oracle big data appliance and solutions
solarisyougood
 
Remote DBA Service: Powering your DBA needs
Remote DBA Service: Powering your DBA needsRemote DBA Service: Powering your DBA needs
Remote DBA Service: Powering your DBA needs
EDB
 
GemFire In Memory Data Grid
GemFire In Memory Data GridGemFire In Memory Data Grid
GemFire In Memory Data Grid
Dmitry Buzdin
 
Expanding with EDB Postgres Advanced Server 9.5
Expanding with EDB Postgres Advanced Server 9.5Expanding with EDB Postgres Advanced Server 9.5
Expanding with EDB Postgres Advanced Server 9.5
EDB
 
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
Cloud Migration Paths: Kubernetes, IaaS, or DBaaSCloud Migration Paths: Kubernetes, IaaS, or DBaaS
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
EDB
 
Which Postgres is Right for You?
Which Postgres is Right for You? Which Postgres is Right for You?
Which Postgres is Right for You?
EDB
 
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
SL Corporation
 
Debunking Common Myths of Hadoop Backup & Test Data Management
Debunking Common Myths of Hadoop Backup & Test Data ManagementDebunking Common Myths of Hadoop Backup & Test Data Management
Debunking Common Myths of Hadoop Backup & Test Data Management
Imanis Data
 
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XDScale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
VMware Tanzu
 

What's hot (20)

Oracle Coherence: in-memory datagrid
Oracle Coherence: in-memory datagridOracle Coherence: in-memory datagrid
Oracle Coherence: in-memory datagrid
 
In memory grids IMDG
In memory grids IMDGIn memory grids IMDG
In memory grids IMDG
 
Hazelcast for Terracotta Users
Hazelcast for Terracotta UsersHazelcast for Terracotta Users
Hazelcast for Terracotta Users
 
5 Advantages of EDB's RemoteDBA Services
5 Advantages of EDB's RemoteDBA Services5 Advantages of EDB's RemoteDBA Services
5 Advantages of EDB's RemoteDBA Services
 
In Memory Data Grids, Demystified!
In Memory Data Grids, Demystified! In Memory Data Grids, Demystified!
In Memory Data Grids, Demystified!
 
Oracle Coherence
Oracle CoherenceOracle Coherence
Oracle Coherence
 
Oracle Coherence
Oracle CoherenceOracle Coherence
Oracle Coherence
 
Best Practices & Lessons Learned from Deployment of PostgreSQL
 Best Practices & Lessons Learned from Deployment of PostgreSQL Best Practices & Lessons Learned from Deployment of PostgreSQL
Best Practices & Lessons Learned from Deployment of PostgreSQL
 
Migration DB2 to EDB - Project Experience
 Migration DB2 to EDB - Project Experience Migration DB2 to EDB - Project Experience
Migration DB2 to EDB - Project Experience
 
Best practices: running high-performance databases on Kubernetes
Best practices: running high-performance databases on KubernetesBest practices: running high-performance databases on Kubernetes
Best practices: running high-performance databases on Kubernetes
 
Active/Active Database Solutions with Log Based Replication in xDB 6.0
Active/Active Database Solutions with Log Based Replication in xDB 6.0Active/Active Database Solutions with Log Based Replication in xDB 6.0
Active/Active Database Solutions with Log Based Replication in xDB 6.0
 
Oracle big data appliance and solutions
Oracle big data appliance and solutionsOracle big data appliance and solutions
Oracle big data appliance and solutions
 
Remote DBA Service: Powering your DBA needs
Remote DBA Service: Powering your DBA needsRemote DBA Service: Powering your DBA needs
Remote DBA Service: Powering your DBA needs
 
GemFire In Memory Data Grid
GemFire In Memory Data GridGemFire In Memory Data Grid
GemFire In Memory Data Grid
 
Expanding with EDB Postgres Advanced Server 9.5
Expanding with EDB Postgres Advanced Server 9.5Expanding with EDB Postgres Advanced Server 9.5
Expanding with EDB Postgres Advanced Server 9.5
 
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
Cloud Migration Paths: Kubernetes, IaaS, or DBaaSCloud Migration Paths: Kubernetes, IaaS, or DBaaS
Cloud Migration Paths: Kubernetes, IaaS, or DBaaS
 
Which Postgres is Right for You?
Which Postgres is Right for You? Which Postgres is Right for You?
Which Postgres is Right for You?
 
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
10 Tricks to Ensure Your Oracle Coherence Cluster is Not a "Black Box" in Pro...
 
Debunking Common Myths of Hadoop Backup & Test Data Management
Debunking Common Myths of Hadoop Backup & Test Data ManagementDebunking Common Myths of Hadoop Backup & Test Data Management
Debunking Common Myths of Hadoop Backup & Test Data Management
 
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XDScale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
Scale Out Your Big Data Apps: The Latest on Pivotal GemFire and GemFire XD
 

Similar to Time to Make the Move to In-Memory Data Grids

Assessing New Database Capabilities – Multi-Model
Assessing New Database Capabilities – Multi-ModelAssessing New Database Capabilities – Multi-Model
Assessing New Database Capabilities – Multi-Model
DATAVERSITY
 
An Introduction to Apache Geode (incubating)
An Introduction to Apache Geode (incubating)An Introduction to Apache Geode (incubating)
An Introduction to Apache Geode (incubating)
Anthony Baker
 
Open Sourcing GemFire - Apache Geode
Open Sourcing GemFire - Apache GeodeOpen Sourcing GemFire - Apache Geode
Open Sourcing GemFire - Apache Geode
Apache Geode
 
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
 Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ... Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
Cloudera, Inc.
 
InfoSphere BigInsights
InfoSphere BigInsightsInfoSphere BigInsights
InfoSphere BigInsights
Wilfried Hoge
 
Cloud Computing Gets Put to the Test
Cloud Computing Gets Put to the TestCloud Computing Gets Put to the Test
Cloud Computing Gets Put to the Test
Avere Systems
 
2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics
DATAVERSITY
 
Using Data Platforms That Are Fit-For-Purpose
Using Data Platforms That Are Fit-For-PurposeUsing Data Platforms That Are Fit-For-Purpose
Using Data Platforms That Are Fit-For-Purpose
DATAVERSITY
 
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaIs your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Cloudera, Inc.
 
Data Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced AnalyticsData Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced Analytics
DATAVERSITY
 
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
Agile Testing Alliance
 
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
Tyler Wishnoff
 
Capgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with ClouderaCapgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with Cloudera
Capgemini
 
Belgium & Luxembourg dedicated online Data Virtualization discovery workshop
Belgium & Luxembourg dedicated online Data Virtualization discovery workshopBelgium & Luxembourg dedicated online Data Virtualization discovery workshop
Belgium & Luxembourg dedicated online Data Virtualization discovery workshop
Denodo
 
e-IT exec lunch - "It's all about data" - 25 May '16
e-IT exec lunch - "It's all about data" - 25 May '16e-IT exec lunch - "It's all about data" - 25 May '16
e-IT exec lunch - "It's all about data" - 25 May '16
Devin Deen
 
Embedded-ml(ai)applications - Bjoern Staender
Embedded-ml(ai)applications - Bjoern StaenderEmbedded-ml(ai)applications - Bjoern Staender
Embedded-ml(ai)applications - Bjoern Staender
Dataconomy Media
 
Google Cloud Platform
Google Cloud PlatformGoogle Cloud Platform
Google Cloud Platform
GeneXus
 
The Shifting Landscape of Data Integration
The Shifting Landscape of Data IntegrationThe Shifting Landscape of Data Integration
The Shifting Landscape of Data Integration
DATAVERSITY
 
Building a Modern Analytic Database with Cloudera 5.8
Building a Modern Analytic Database with Cloudera 5.8Building a Modern Analytic Database with Cloudera 5.8
Building a Modern Analytic Database with Cloudera 5.8
Cloudera, Inc.
 
SQL Server 2019 Data Virtualization
SQL Server 2019 Data VirtualizationSQL Server 2019 Data Virtualization
SQL Server 2019 Data Virtualization
Matthew W. Bowers
 

Similar to Time to Make the Move to In-Memory Data Grids (20)

Assessing New Database Capabilities – Multi-Model
Assessing New Database Capabilities – Multi-ModelAssessing New Database Capabilities – Multi-Model
Assessing New Database Capabilities – Multi-Model
 
An Introduction to Apache Geode (incubating)
An Introduction to Apache Geode (incubating)An Introduction to Apache Geode (incubating)
An Introduction to Apache Geode (incubating)
 
Open Sourcing GemFire - Apache Geode
Open Sourcing GemFire - Apache GeodeOpen Sourcing GemFire - Apache Geode
Open Sourcing GemFire - Apache Geode
 
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
 Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ... Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
Gartner Data and Analytics Summit: Bringing Self-Service BI & SQL Analytics ...
 
InfoSphere BigInsights
InfoSphere BigInsightsInfoSphere BigInsights
InfoSphere BigInsights
 
Cloud Computing Gets Put to the Test
Cloud Computing Gets Put to the TestCloud Computing Gets Put to the Test
Cloud Computing Gets Put to the Test
 
2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics2022 Trends in Enterprise Analytics
2022 Trends in Enterprise Analytics
 
Using Data Platforms That Are Fit-For-Purpose
Using Data Platforms That Are Fit-For-PurposeUsing Data Platforms That Are Fit-For-Purpose
Using Data Platforms That Are Fit-For-Purpose
 
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaIs your big data journey stalling? Take the Leap with Capgemini and Cloudera
Is your big data journey stalling? Take the Leap with Capgemini and Cloudera
 
Data Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced AnalyticsData Architecture Best Practices for Advanced Analytics
Data Architecture Best Practices for Advanced Analytics
 
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
 
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
AI-Powered Analytics: What It Is and How It’s Powering the Next Generation of...
 
Capgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with ClouderaCapgemini Leap Data Transformation Framework with Cloudera
Capgemini Leap Data Transformation Framework with Cloudera
 
Belgium & Luxembourg dedicated online Data Virtualization discovery workshop
Belgium & Luxembourg dedicated online Data Virtualization discovery workshopBelgium & Luxembourg dedicated online Data Virtualization discovery workshop
Belgium & Luxembourg dedicated online Data Virtualization discovery workshop
 
e-IT exec lunch - "It's all about data" - 25 May '16
e-IT exec lunch - "It's all about data" - 25 May '16e-IT exec lunch - "It's all about data" - 25 May '16
e-IT exec lunch - "It's all about data" - 25 May '16
 
Embedded-ml(ai)applications - Bjoern Staender
Embedded-ml(ai)applications - Bjoern StaenderEmbedded-ml(ai)applications - Bjoern Staender
Embedded-ml(ai)applications - Bjoern Staender
 
Google Cloud Platform
Google Cloud PlatformGoogle Cloud Platform
Google Cloud Platform
 
The Shifting Landscape of Data Integration
The Shifting Landscape of Data IntegrationThe Shifting Landscape of Data Integration
The Shifting Landscape of Data Integration
 
Building a Modern Analytic Database with Cloudera 5.8
Building a Modern Analytic Database with Cloudera 5.8Building a Modern Analytic Database with Cloudera 5.8
Building a Modern Analytic Database with Cloudera 5.8
 
SQL Server 2019 Data Virtualization
SQL Server 2019 Data VirtualizationSQL Server 2019 Data Virtualization
SQL Server 2019 Data Virtualization
 

More from Hazelcast

The Power of the JVM: Applied Polyglot Projects with Java and JavaScript
The Power of the JVM: Applied Polyglot Projects with Java and JavaScriptThe Power of the JVM: Applied Polyglot Projects with Java and JavaScript
The Power of the JVM: Applied Polyglot Projects with Java and JavaScript
Hazelcast
 
JCache - It's finally here
JCache -  It's finally hereJCache -  It's finally here
JCache - It's finally here
Hazelcast
 
Speed Up Your Existing Relational Databases with Hazelcast and Speedment
Speed Up Your Existing Relational Databases with Hazelcast and SpeedmentSpeed Up Your Existing Relational Databases with Hazelcast and Speedment
Speed Up Your Existing Relational Databases with Hazelcast and Speedment
Hazelcast
 
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorganShared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
Hazelcast
 
Applying Real-time SQL Changes in your Hazelcast Data Grid
Applying Real-time SQL Changes in your Hazelcast Data GridApplying Real-time SQL Changes in your Hazelcast Data Grid
Applying Real-time SQL Changes in your Hazelcast Data Grid
Hazelcast
 
WAN Replication: Hazelcast Enterprise Lightning Talk
WAN Replication: Hazelcast Enterprise Lightning TalkWAN Replication: Hazelcast Enterprise Lightning Talk
WAN Replication: Hazelcast Enterprise Lightning Talk
Hazelcast
 
JAAS Security Suite: Hazelcast Enterprise Lightning Talk
JAAS Security Suite: Hazelcast Enterprise Lightning TalkJAAS Security Suite: Hazelcast Enterprise Lightning Talk
JAAS Security Suite: Hazelcast Enterprise Lightning Talk
Hazelcast
 
Extreme Network Performance with Hazelcast on Torusware
Extreme Network Performance with Hazelcast on ToruswareExtreme Network Performance with Hazelcast on Torusware
Extreme Network Performance with Hazelcast on Torusware
Hazelcast
 
JAXLondon - Squeezing Performance of IMDGs
JAXLondon - Squeezing Performance of IMDGsJAXLondon - Squeezing Performance of IMDGs
JAXLondon - Squeezing Performance of IMDGs
Hazelcast
 
OrientDB & Hazelcast: In-Memory Distributed Graph Database
 OrientDB & Hazelcast: In-Memory Distributed Graph Database OrientDB & Hazelcast: In-Memory Distributed Graph Database
OrientDB & Hazelcast: In-Memory Distributed Graph Database
Hazelcast
 
How to Use HazelcastMQ for Flexible Messaging and More
 How to Use HazelcastMQ for Flexible Messaging and More How to Use HazelcastMQ for Flexible Messaging and More
How to Use HazelcastMQ for Flexible Messaging and More
Hazelcast
 
Devoxx UK 2014 High Performance In-Memory Java with Open Source
Devoxx UK 2014   High Performance In-Memory Java with Open SourceDevoxx UK 2014   High Performance In-Memory Java with Open Source
Devoxx UK 2014 High Performance In-Memory Java with Open Source
Hazelcast
 
JSR107 State of the Union JavaOne 2013
JSR107  State of the Union JavaOne 2013JSR107  State of the Union JavaOne 2013
JSR107 State of the Union JavaOne 2013
Hazelcast
 
Jfokus - Hazlecast
Jfokus - HazlecastJfokus - Hazlecast
Jfokus - Hazlecast
Hazelcast
 
In-memory No SQL- GIDS2014
In-memory No SQL- GIDS2014In-memory No SQL- GIDS2014
In-memory No SQL- GIDS2014
Hazelcast
 
In-memory Data Management Trends & Techniques
In-memory Data Management Trends & TechniquesIn-memory Data Management Trends & Techniques
In-memory Data Management Trends & Techniques
Hazelcast
 
How to Speed up your Database
How to Speed up your DatabaseHow to Speed up your Database
How to Speed up your Database
Hazelcast
 
Hazelcast HUGL
Hazelcast HUGLHazelcast HUGL
Hazelcast HUGL
Hazelcast
 
Devoxx 2013 - Hazelcast
Devoxx 2013 - Hazelcast Devoxx 2013 - Hazelcast
Devoxx 2013 - Hazelcast
Hazelcast
 
Clustering your Application with Hazelcast
Clustering your Application with HazelcastClustering your Application with Hazelcast
Clustering your Application with Hazelcast
Hazelcast
 

More from Hazelcast (20)

The Power of the JVM: Applied Polyglot Projects with Java and JavaScript
The Power of the JVM: Applied Polyglot Projects with Java and JavaScriptThe Power of the JVM: Applied Polyglot Projects with Java and JavaScript
The Power of the JVM: Applied Polyglot Projects with Java and JavaScript
 
JCache - It's finally here
JCache -  It's finally hereJCache -  It's finally here
JCache - It's finally here
 
Speed Up Your Existing Relational Databases with Hazelcast and Speedment
Speed Up Your Existing Relational Databases with Hazelcast and SpeedmentSpeed Up Your Existing Relational Databases with Hazelcast and Speedment
Speed Up Your Existing Relational Databases with Hazelcast and Speedment
 
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorganShared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
Shared Memory Performance: Beyond TCP/IP with Ben Cotton, JPMorgan
 
Applying Real-time SQL Changes in your Hazelcast Data Grid
Applying Real-time SQL Changes in your Hazelcast Data GridApplying Real-time SQL Changes in your Hazelcast Data Grid
Applying Real-time SQL Changes in your Hazelcast Data Grid
 
WAN Replication: Hazelcast Enterprise Lightning Talk
WAN Replication: Hazelcast Enterprise Lightning TalkWAN Replication: Hazelcast Enterprise Lightning Talk
WAN Replication: Hazelcast Enterprise Lightning Talk
 
JAAS Security Suite: Hazelcast Enterprise Lightning Talk
JAAS Security Suite: Hazelcast Enterprise Lightning TalkJAAS Security Suite: Hazelcast Enterprise Lightning Talk
JAAS Security Suite: Hazelcast Enterprise Lightning Talk
 
Extreme Network Performance with Hazelcast on Torusware
Extreme Network Performance with Hazelcast on ToruswareExtreme Network Performance with Hazelcast on Torusware
Extreme Network Performance with Hazelcast on Torusware
 
JAXLondon - Squeezing Performance of IMDGs
JAXLondon - Squeezing Performance of IMDGsJAXLondon - Squeezing Performance of IMDGs
JAXLondon - Squeezing Performance of IMDGs
 
OrientDB & Hazelcast: In-Memory Distributed Graph Database
 OrientDB & Hazelcast: In-Memory Distributed Graph Database OrientDB & Hazelcast: In-Memory Distributed Graph Database
OrientDB & Hazelcast: In-Memory Distributed Graph Database
 
How to Use HazelcastMQ for Flexible Messaging and More
 How to Use HazelcastMQ for Flexible Messaging and More How to Use HazelcastMQ for Flexible Messaging and More
How to Use HazelcastMQ for Flexible Messaging and More
 
Devoxx UK 2014 High Performance In-Memory Java with Open Source
Devoxx UK 2014   High Performance In-Memory Java with Open SourceDevoxx UK 2014   High Performance In-Memory Java with Open Source
Devoxx UK 2014 High Performance In-Memory Java with Open Source
 
JSR107 State of the Union JavaOne 2013
JSR107  State of the Union JavaOne 2013JSR107  State of the Union JavaOne 2013
JSR107 State of the Union JavaOne 2013
 
Jfokus - Hazlecast
Jfokus - HazlecastJfokus - Hazlecast
Jfokus - Hazlecast
 
In-memory No SQL- GIDS2014
In-memory No SQL- GIDS2014In-memory No SQL- GIDS2014
In-memory No SQL- GIDS2014
 
In-memory Data Management Trends & Techniques
In-memory Data Management Trends & TechniquesIn-memory Data Management Trends & Techniques
In-memory Data Management Trends & Techniques
 
How to Speed up your Database
How to Speed up your DatabaseHow to Speed up your Database
How to Speed up your Database
 
Hazelcast HUGL
Hazelcast HUGLHazelcast HUGL
Hazelcast HUGL
 
Devoxx 2013 - Hazelcast
Devoxx 2013 - Hazelcast Devoxx 2013 - Hazelcast
Devoxx 2013 - Hazelcast
 
Clustering your Application with Hazelcast
Clustering your Application with HazelcastClustering your Application with Hazelcast
Clustering your Application with Hazelcast
 

Recently uploaded

Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfTop Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
VALiNTRY360
 
Odoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
Odoo ERP Vs. Traditional ERP Systems – A Comparative AnalysisOdoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
Odoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
Envertis Software Solutions
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Neo4j
 
ALGIT - Assembly Line for Green IT - Numbers, Data, Facts
ALGIT - Assembly Line for Green IT - Numbers, Data, FactsALGIT - Assembly Line for Green IT - Numbers, Data, Facts
ALGIT - Assembly Line for Green IT - Numbers, Data, Facts
Green Software Development
 
What is Master Data Management by PiLog Group
What is Master Data Management by PiLog GroupWhat is Master Data Management by PiLog Group
What is Master Data Management by PiLog Group
aymanquadri279
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j
 
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Łukasz Chruściel
 
Microservice Teams - How the cloud changes the way we work
Microservice Teams - How the cloud changes the way we workMicroservice Teams - How the cloud changes the way we work
Microservice Teams - How the cloud changes the way we work
Sven Peters
 
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CDKuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
rodomar2
 
OpenMetadata Community Meeting - 5th June 2024
OpenMetadata Community Meeting - 5th June 2024OpenMetadata Community Meeting - 5th June 2024
OpenMetadata Community Meeting - 5th June 2024
OpenMetadata
 
Lecture 2 - software testing SE 412.pptx
Lecture 2 - software testing SE 412.pptxLecture 2 - software testing SE 412.pptx
Lecture 2 - software testing SE 412.pptx
TaghreedAltamimi
 
Transform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR SolutionsTransform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR Solutions
TheSMSPoint
 
Webinar On-Demand: Using Flutter for Embedded
Webinar On-Demand: Using Flutter for EmbeddedWebinar On-Demand: Using Flutter for Embedded
Webinar On-Demand: Using Flutter for Embedded
ICS
 
Fundamentals of Programming and Language Processors
Fundamentals of Programming and Language ProcessorsFundamentals of Programming and Language Processors
Fundamentals of Programming and Language Processors
Rakesh Kumar R
 
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeA Study of Variable-Role-based Feature Enrichment in Neural Models of Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
Aftab Hussain
 
WWDC 2024 Keynote Review: For CocoaCoders Austin
WWDC 2024 Keynote Review: For CocoaCoders AustinWWDC 2024 Keynote Review: For CocoaCoders Austin
WWDC 2024 Keynote Review: For CocoaCoders Austin
Patrick Weigel
 
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
mz5nrf0n
 
UI5con 2024 - Bring Your Own Design System
UI5con 2024 - Bring Your Own Design SystemUI5con 2024 - Bring Your Own Design System
UI5con 2024 - Bring Your Own Design System
Peter Muessig
 
Graspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code AnalysisGraspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code Analysis
Aftab Hussain
 
Mobile App Development Company In Noida | Drona Infotech
Mobile App Development Company In Noida | Drona InfotechMobile App Development Company In Noida | Drona Infotech
Mobile App Development Company In Noida | Drona Infotech
Drona Infotech
 

Recently uploaded (20)

Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfTop Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdf
 
Odoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
Odoo ERP Vs. Traditional ERP Systems – A Comparative AnalysisOdoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
Odoo ERP Vs. Traditional ERP Systems – A Comparative Analysis
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
 
ALGIT - Assembly Line for Green IT - Numbers, Data, Facts
ALGIT - Assembly Line for Green IT - Numbers, Data, FactsALGIT - Assembly Line for Green IT - Numbers, Data, Facts
ALGIT - Assembly Line for Green IT - Numbers, Data, Facts
 
What is Master Data Management by PiLog Group
What is Master Data Management by PiLog GroupWhat is Master Data Management by PiLog Group
What is Master Data Management by PiLog Group
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
 
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Need for Speed: Removing speed bumps from your Symfony projects ⚡️
Need for Speed: Removing speed bumps from your Symfony projects ⚡️
 
Microservice Teams - How the cloud changes the way we work
Microservice Teams - How the cloud changes the way we workMicroservice Teams - How the cloud changes the way we work
Microservice Teams - How the cloud changes the way we work
 
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CDKuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
KuberTENes Birthday Bash Guadalajara - Introducción a Argo CD
 
OpenMetadata Community Meeting - 5th June 2024
OpenMetadata Community Meeting - 5th June 2024OpenMetadata Community Meeting - 5th June 2024
OpenMetadata Community Meeting - 5th June 2024
 
Lecture 2 - software testing SE 412.pptx
Lecture 2 - software testing SE 412.pptxLecture 2 - software testing SE 412.pptx
Lecture 2 - software testing SE 412.pptx
 
Transform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR SolutionsTransform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR Solutions
 
Webinar On-Demand: Using Flutter for Embedded
Webinar On-Demand: Using Flutter for EmbeddedWebinar On-Demand: Using Flutter for Embedded
Webinar On-Demand: Using Flutter for Embedded
 
Fundamentals of Programming and Language Processors
Fundamentals of Programming and Language ProcessorsFundamentals of Programming and Language Processors
Fundamentals of Programming and Language Processors
 
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeA Study of Variable-Role-based Feature Enrichment in Neural Models of Code
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
 
WWDC 2024 Keynote Review: For CocoaCoders Austin
WWDC 2024 Keynote Review: For CocoaCoders AustinWWDC 2024 Keynote Review: For CocoaCoders Austin
WWDC 2024 Keynote Review: For CocoaCoders Austin
 
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
原版定制美国纽约州立大学奥尔巴尼分校毕业证学位证书原版一模一样
 
UI5con 2024 - Bring Your Own Design System
UI5con 2024 - Bring Your Own Design SystemUI5con 2024 - Bring Your Own Design System
UI5con 2024 - Bring Your Own Design System
 
Graspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code AnalysisGraspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code Analysis
 
Mobile App Development Company In Noida | Drona Infotech
Mobile App Development Company In Noida | Drona InfotechMobile App Development Company In Noida | Drona Infotech
Mobile App Development Company In Noida | Drona Infotech
 

Time to Make the Move to In-Memory Data Grids

  • 1. © 2015 Hazelcast Inc. It’s Time to Make the Move to In-Memory Data Grids
 Featuring Greg Luck, Forrester Research’s Mike Gualtieri, and 
 Ellie Mae’s Ken Kolda
  • 2. © 2015 Hazelcast Inc. Featuring 2 GREG LUCK CEO, HAZELCAST MIKE GUALTIERI PRINCIPAL ANALYST, FORRESTER RESEARCH KEN KOLDA SOFTWARE ARCHITECT, ELLIE MAE
  • 3. Make The Move To In-Memory Data Grids Mike Gualtieri, Principal Analyst July 16, 2015 Twitter: @mgualtieri
  • 4. Planning, implementing, or expanding the use of in-memory data platform. 73% Base: 1,805 global data and analytics decision-makers Source: Forrester Global Business Technographics Data And Analytics Online Survey, 2015
  • 6. © 2015 Forrester Research, Inc. Reproduction Prohibited 6 52% 53% 53% 54% 58% 64% 64% 65% 66% 73% 75% 0% 10% 20% 30% 40% 50% 60% 70% 80% Better leverage big data and analytics in business decision- Create a comprehensive strategy for addressing digital Create a comprehensive digital marketing strategy Better comply with regulations and requirements Improve differentiation in the market Increase influence and brand reach in the market Address rising customer expectations Improve our ability to innovate Reduce costs Improve our products /services Improve the experience of our customers Customer experience is a top business priority over the next 12 months Base: 3,005 global data and analytics decision-makers Source: Global Business Technographics Data And Analytics Online Survey, 2015
  • 7. For you For all For segments For you CRM Hyper-Personal, Real-Time Digital Experiences Personal Relationships Mass Production CustomerExperience 1800 1900 1950 2000 2015
  • 9. Customers want and increasingly expect to be treated like celebrities.
  • 10. •  Use analytics to learn customer characteristics and behavior •  Detect real-time context •  Adapt applications to serve an individual customer Celebrity experiences must: Be Blazing Fast
  • 12. Ubiquitous, near-zero latency for even the most complex data and compute operations.
  • 13. DEFINITION FORRESTERTechnologies that are principally architected to use chip-based memory to accelerate the performance of data access and applications; and reduce the complexity of app development.
  • 14. Scale should not limit design decisions.
  • 18. In-memory must fit and work seamlessly with existing architectures.
  • 19. In-Memory technology speeds application development by reducing architectural concerns.
  • 21. 73%
  • 23. What if you had ubiquitous, near-zero latency for even the most complex data and compute operations?
  • 25. © 2015 Forrester Research, Inc. Reproduction Prohibited 25 G GG S S S Streaming Analytics B B B General-purpose data processing cluster D Scale-up Database Data And Compute Grid DDD Clustered Database
  • 27. Overcome legacy architectural bottlenecks such as databases.
  • 28. Real-time integration for shared cache.
  • 31. HAZELCAST  @  ELLIE  MAE Ken  Kolda SOFTWARE  ARCHITECT
  • 32. About  Ellie  Mae •  Founded  in  1997  to  provide  soDware  soluFons  to  mortgage   industry •  Released  Encompass  loan  originaFon  system  in  2003 •  Boxed,  on-­‐premise  soDware  sold  in  retail  stores •  Target  market  was  2  –  20  user  mortgage  broker •  Started  offering  Hosted  model  in  2007 •  Relieved  customers  from  burden  of  IT  infrastructure,  processes •  Roughly  80%  of  customers  currently  use  Hosted  model,  with  customers  up   to  3000  users •  Began  engineering  of  “Next  Gen”  soluFon  in  2013 •  Hybrid  cloud  model  for  truly  SaaS  soluFon 7/22/15 ©2015  Ellie  Mae.  All  rights  reserved.   32
  • 33. 7/22/15 ©2015  Ellie  Mae.  All  rights  reserved.   33 The  Problem  of  Scale •  Legacy  Architecture •  .NET-­‐based  client/server  applicaFon  with   SQL  Server  back-­‐end •  Designed  for  on-­‐premise,  single-­‐tenant   deployment •  Scalability  Limits •  Server  adapted  to  support  limited  mulF-­‐ tenancy •  Home-­‐grown,  in-­‐process  caching  added   to  ease  load  on  SQL  Server •  Cache  synchronizaFon  issues  prevent   horizontal  scale,  load  balancing Data Store Encompass  Clients Write Read Encompass   Server Cache Encompass   Server Cache Encompass   Server Cache Data Store Encompass  Clients Write Read Encompass   Server Encompass   Server Encompass  Clients Write Read Data Store
  • 34. 7/22/15 ©2015  Ellie  Mae.  All  rights  reserved.   34 Horizontal  Scale  via  Hazelcast •  Distributed  Cache  Tier •  In-­‐process  cache  replaced  with   shared  Hazelcast  data  grid •  Hazelcast  locking  used  to  ensure   transacFonal  consistency  between   server  nodes •  Scalability  &  Availability •  App  Fer  can  now  scale  horizontally •  EliminaFon  of  single  point  of  failure •  App  servers  can  be  brought  up/ down  without  loss  of  cache •  Hazelcast  cluster  can  be  expanded   to  meet  future  demands Encompass   Server Encompass   Server Encompass  Clients Write Read Data Store
  • 35. 7/22/15 ©2015  Ellie  Mae.  All  rights  reserved.   35 Choosing  Hazelcast •  Requirements/Use  cases •  Database  caching:  Cross-­‐process  locks,  Hibernate  second-­‐level  caching •  Session  storage:  TTL  and  Idle  Time  support,  evicFon/expiraFon  noFficaFons   &  policies •  NaFve  support  for  .NET,  Java  clients;  REST  support •  High-­‐performance,  highly  available,  horizontally  scalable •  Enterprise  support •  EvaluaFon  process •  High-­‐level  evaluaFon  of  8  in-­‐memory  data  grids  (JDG,  Couchbase,  JvCache,   Terracona,  Riak,  Redis,  Memcached) •  Six-­‐month  PoC  on  top  three  contenders  (Hazelcast,  JDG,  JvCache) •  Rated  on  criteria  including  performance,  fault  tolerance,  client  support,   ease-­‐of-­‐configuraFon/operaFon,  monitoring,  noFficaFons
  • 36. 7/22/15 ©2015  Ellie  Mae.  All  rights  reserved.   36 EvaluaFon  Results *  Note:  Evalua-on  performed  using  Hazelcast  3.0