addressalign-toparrow-leftarrow-rightbackbellblockcalendarcameraccwcheckchevron-downchevron-leftchevron-rightchevron-small-downchevron-small-leftchevron-small-rightchevron-small-upchevron-upcircle-with-checkcircle-with-crosscircle-with-pluscrossdots-three-verticaleditemptyheartexporteye-with-lineeyefacebookfolderfullheartglobegmailgooglegroupshelp-with-circleimageimagesinstagramlinklocation-pinm-swarmSearchmailmessagesminusmoremuplabelShape 3 + Rectangle 1ShapeoutlookpersonJoin Group on CardStartprice-ribbonShapeShapeShapeShapeImported LayersImported LayersImported Layersshieldstartickettrashtriangle-downtriangle-uptwitteruserwarningyahoo

[Online] Hazelcast: In-Memory Data Grid Without Black Magic

  • May 7, 2015 · 8:00 PM
  • This location is shown only to members

Abstract:
In-Memory Data Grids (or IMDGs in short) have historically been the exclusive domain of large Investment Banks and proprietary solutions such as Oracle Coherence, VMWare Pivotal Gemfire and Software AG Terracotta. Hazelcast provides the leading open source alternative to these solutions, and is helping to support the democratization of Data Grid technology across a much wider range of vertical industries including telco, gaming, travel, ecommerce, software, life sciences, health care and many more.

What is an In-Memory Data Grid?
An In-Memory Data Grid is data management software that enables:

* Scale-out Computing: every node adds their CPU and RAM to the cluster, which can be used by all nodes
* Resilience: nodes can fail randomly without data loss while minimizing performance impact to running applications
* Programming Model: a way for developers to easily program the cluster of machines as if it were a single machine
* Fast, Big Data: it enables very large data sets to be manipulated in main memory
* Dynamic Scalability: nodes (computers) can dynamically join the other computers in a grid (cluster)
* Elastic Main Memory: every node adds their RAM to the cluster’s memory pool

In-Memory Data Grids are often used with Databases in order to improve performance of applications, to distribute data across servers, clusters and geographies and to manage very large data sets or very high data ingest rates.

No prior knowledge of IMDBs or Hazelcast required!

Speaker:

Viktor Gamov, Senior Solutions Architect at Hazelcast

Viktor joined Hazelcast with over 5 years experience of architecting and building the enterprise applications using open source technologies. At his previous roles, he helped the financial companies and startups with various Java and HTML5 projects. He holds MS in Computer Science. He is a co-author of the O’Reilly book «Enterprise Web Development. From Desktop To Mobile». Viktor presented at various international conferences (http://lanyrd.com/gamussa) on Java and JavaScript related topics. He tweets at @gamussa.

Join or login to comment.

  • Denis T.

    1h is just not enough for material and discussion we probably should shoot for 2h next time

    1 · May 8, 2015

    • Viktor G.

      Thanks Denis. Online session has pros and cons. It's technically impossible to fit everything into just one session. That is why I have started Hazelcast user group as separate entity.

      May 8, 2015

    • Viktor G.

      New meetup. Not sure if you able to join http://www.meetup.com...­

      July 7, 2015

  • Viktor G.

    Guys, I hope you enjoyed this session. We have another Hazelcast event next month in NYC at Intercontinental Exchange (ICE). Details and RSVP here http://www.meetup.com/hug-nyc/events/223530005/

    June 29, 2015

Our Sponsors

  • Farata Systems

    This sponsor pays subscription fees for this meetup and online sessions.

  • TigerLabs

    TigerLabs offers the meeting space for Princeton JUG.

  • Hazelcast

    food and beverages, venue fees

People in this
Meetup are also in:

Sign up

Meetup members, Log in

By clicking "Sign up" or "Sign up using Facebook", you confirm that you accept our Terms of Service & Privacy Policy