Introducing Infinispan
Manik Surtani
Founder and Project Lead, Infinispan
“There is a need for a viable cloud-ready
  data store. People need to rethink the
  way they organise, store and access
 ...
Who is Manik?
R&D Engineer, Red Hat
  Founder and project lead, Infinispan
  Project lead, JBoss Cache
  Contributor on var...
Clouds are today!

Clouds are happening
  *aaS
You cannot escape them!
  Public: Amazon, Google, Rackspace, etc.
  Private...
Why are clouds popular?

Piecemeal costs - pay for what you use, no more!
Economies of scale - everyone benefits
High avail...
Why should I care?
The platforms I use will still be relevant:
  Java, Java EE
  Python, Ruby, .NET
  ... whatever!!
The O...
Data Storage
Databases on clouds don't make sense
  Traditional modes of data storage won't work
  Clouds are inherently s...
Data Storage
Data expansion
  Web 2.0, rich mobile clients, multimedia content
  Databases can’t cope with the volume
Dyna...
A solution: Data Grids!
 Data grids are perfect for clouds
   Highly scalable
   No single point of failure
   Works with ...
Data Grids - Speed!
Very low latency due to minimal disk lookup
Memory 2 orders of magnitude faster than disk
Especially f...
Introducing Infinispan
 Scalable data grid platform
   open source - LGPL
   Based on some JBoss Cache code
   ... but most...
Infinispan != JBoss Cache 4
New Architecture
  Internal data container design completely different
  Cutting edge algorithm...
“Borrowed” from JBoss Cache
 JTA transactions
 Replicated data structure
 Eviction, cache persistence
 Notifications and ev...
… and new features!
Consistent hash based data distribution
Much simpler Map API (JSR-107 compliant)
JPA-like API
Client/s...
… and new features!

Ability to be consumed by non-JVM platforms
JOPR based GUI management console
Distributed execution
 ...
Data distribution
 Consistent hash based data distribution
   Locating entries very efficient
     No network calls
     No...
JPA-like API, fine-grained
replication

Successor to POJO Cache
JPA-like interface: persist, find, remove...
Will not rely o...
Management
Uses JOPR
  Simple WAR file
  Rich web-based GUI
  Open Source (LGPL)
Infinispan likes JMX
  exposes all data, op...
So why is Infinispan sexy?
Why is Infinispan sexy?
Transparent horizontal scalability
  Elastic in both directions
Fast, low latency data access
Abili...
To sum it up
Clouds are becoming mainstream
  Developers need to think about challenges involved
  DBs and clouds pose man...
Thanks for your attention!
http://www.infinispan.org
http://blog.infinispan.org
http://twitter.com/infinispan
  #infinispan on...
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  1. 1. Introducing Infinispan Manik Surtani Founder and Project Lead, Infinispan
  2. 2. “There is a need for a viable cloud-ready data store. People need to rethink the way they organise, store and access data.” • Data grids as cloud data stores • Introducing Infinispan
  3. 3. Who is Manik? R&D Engineer, Red Hat Founder and project lead, Infinispan Project lead, JBoss Cache Contributor on various OSS projects JGroups, Hibernate, JBoss AS, etc. Frequent speaker on data grids, cloud computing and parallelism http://twitter.com/maniksurtani http://blog.infinispan.org
  4. 4. Clouds are today! Clouds are happening *aaS You cannot escape them! Public: Amazon, Google, Rackspace, etc. Private: Eucalyptus, VMWare, IBM, RedHat Clouds will become mainstream Traditional data centres marginalised
  5. 5. Why are clouds popular? Piecemeal costs - pay for what you use, no more! Economies of scale - everyone benefits High availability Implicit backups! Very fast provisioning, elasticity Familiar charging model Controllable costs
  6. 6. Why should I care? The platforms I use will still be relevant: Java, Java EE Python, Ruby, .NET ... whatever!! The OS I use will still be relevant Linux Solaris etc.
  7. 7. Data Storage Databases on clouds don't make sense Traditional modes of data storage won't work Clouds are inherently stateless, ephemeral Scalability is crucial Databases still are a bottleneck … and single point of failure!
  8. 8. Data Storage Data expansion Web 2.0, rich mobile clients, multimedia content Databases can’t cope with the volume Dynamic structure Schema-less designs Partial-schemas
  9. 9. A solution: Data Grids! Data grids are perfect for clouds Highly scalable No single point of failure Works with ephemeral cloud nodes Very low latency Data grids
  10. 10. Data Grids - Speed! Very low latency due to minimal disk lookup Memory 2 orders of magnitude faster than disk Especially for frequently used data Far greater concurrency Disk IO is always a concurrency bottleneck Memory offers far greater concurrency
  11. 11. Introducing Infinispan Scalable data grid platform open source - LGPL Based on some JBoss Cache code ... but mostly all-new Infinispan... ... is a data grid platform ... has a Map-like API - compatible with JSR-107 (JCACHE)
  12. 12. Infinispan != JBoss Cache 4 New Architecture Internal data container design completely different Cutting edge algorithms New APIs APIs completely different Not backward-compatible Although an code-level compatibility layer is available New Expectations and aspirations Designed for a wider scope of purpose
  13. 13. “Borrowed” from JBoss Cache JTA transactions Replicated data structure Eviction, cache persistence Notifications and eventing API JMX reporting Fine-grained replication MVCC locking Non-blocking state transfer techniques Query API
  14. 14. … and new features! Consistent hash based data distribution Much simpler Map API (JSR-107 compliant) JPA-like API Client/server module memcached compatibility HotRod - binary protocol to support “smart clients” REST API REST-* caching spec effort
  15. 15. … and new features! Ability to be consumed by non-JVM platforms JOPR based GUI management console Distributed execution Map/reduce programming model made easy!
  16. 16. Data distribution Consistent hash based data distribution Locating entries very efficient No network calls No need for metadata Will allow us to scale to bigger clusters Goal of efficient scaling to 1000’s of nodes Lightweight, “L1” cache for efficient reads On writes, “L1” gets invalidated Dynamic rebalancing
  17. 17. JPA-like API, fine-grained replication Successor to POJO Cache JPA-like interface: persist, find, remove... Will not rely on AOP, javassist, etc. More robust and easier to use/debug Familiar JPA-like interface Easy migration from existing, “traditional” datastores!
  18. 18. Management Uses JOPR Simple WAR file Rich web-based GUI Open Source (LGPL) Infinispan likes JMX exposes all data, operations in JMX Infinispan-JOPR plugin represents this graphically
  19. 19. So why is Infinispan sexy?
  20. 20. Why is Infinispan sexy? Transparent horizontal scalability Elastic in both directions Fast, low latency data access Ability to address a very large heap Cloud-ready datastore Not just for Java Free and doesn't suck!
  21. 21. To sum it up Clouds are becoming mainstream Developers need to think about challenges involved DBs and clouds pose many challenges Data grids offer a good alternative Infinispan, a new open source data grid Viable cloud data store Not just for clouds: remove bottlenecks and single points of failure in non-cloud environments too
  22. 22. Thanks for your attention! http://www.infinispan.org http://blog.infinispan.org http://twitter.com/infinispan #infinispan on Twitter

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