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GridGain Releases Open Source Java Grid Computing Platform with AOP Enablement

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GridGain Systems has released version 1.0 of their open source Java grid computing platform. Features include:

  • Clear focus on computational or processing grids
  • Developed entirely on Java 5 foundation
  • LGPL Open Source licensed
  • Out-of-the-box integration with JBoss and Spring
  • Unique annotation and AOP-based grid enabling technology

GridGain is a computational grid at this time and does not include data grid functionality.  GridGain supports two main methods of grid enabling the Java application.  A grid task can be created, packaged into a GAR file (much the same way as you package your WAR/JAR/EAR files) and deploying it into GridGain.  Grid functionality can also be AOP-based using either AspectJ, SpringAOP or JBoss AOP frameworks to cross-cut existing code and inject gridifying logic. With AOP peer-to-peer hot (re)deployment is provided to distribute tasks.

GridGain not only provides grid related processing APIs but also pluggable service provider implementations for other common grid related services such as:

  • Communication
  • Discovery
  • Deployment
  • Events
  • Checkpoints
  • Collision
The roadmap for version 1.1 lists support and enhanced integration with Tangosol Coherence, BEA Weblogic, IBM WebSphere, and Mule ESB.

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Community comments

  • Congrats!

    by Cameron Purdy /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    Nikita et al - glad to see the release, after so much work (over the long we've been talking about it). Congratulations!

    Peace,

    Cameron Purdy
    Tangosol Coherence: The Java Data Grid

  • Re: Congrats!

    by Nikita Ivanov /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    Thanks Cameron,
    It was longer than we anticipated and things changed. But the project now has a solid development community around globe. Hopefully, this project will strive and we’ll see new features and innovation in it.

    Nikita.

  • How does this compare with GigaSpaces?

    by Satadru Roy /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    Pardon my ignorance but how does GridGain compare with a JavaSpace implementation such as GigaSpaces? I have only very high level idea but doesn't JavaSpace also support this master-worker pattern, potentially distributed over multiple nodes?

  • Re: How does this compare with GigaSpaces?

    by Cameron Purdy /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    .. doesn't JavaSpace also support this master-worker pattern ..?


    JavaSpaces supports the master-worker pattern. If you are interested in integrating an open source JavaSpaces implementation into GridGain, then you should check out Blitz:

    www.dancres.org/blitz/

    Peace,

    Cameron Purdy
    Tangosol Coherence: The Java Data Grid

  • Re: How does this compare with GigaSpaces?

    by Nikita Ivanov /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    I think the main difference is GridGain's focus on processing or computational grids while GigaSpaces is focusing more on data grids (e.g. distributed caching). JavaSpaces is just an implementation detail that GigaSpaces chose to use (Coherence is data grid too but doesn't use JavaSpaces for its implementation).

    I'm not sure master-worker is a good analogy. I often say that split-aggregate or broadcast-reduce (in MPI speak) is a better way to describe the idea behind processing grids.

    Best,
    Nikita.

  • Re: How does this compare with GigaSpaces?

    by Jason Carreira /

    Your message is awaiting moderation. Thank you for participating in the discussion.

    I think the main difference is GridGain's focus on processing or computational grids while GigaSpaces is focusing more on data grids (e.g. distributed caching). JavaSpaces is just an implementation detail that GigaSpaces chose to use (Coherence is data grid too but doesn't use JavaSpaces for its implementation).

    I'm not sure master-worker is a good analogy. I often say that split-aggregate or broadcast-reduce (in MPI speak) is a better way to describe the idea behind processing grids.

    Best,
    Nikita.


    Is that like Map-Reduce? That could be interesting....

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