GridGain's In-Memory Data Fabric entered Apache Incubator last October under the name of Apache Ignite. The company donated its flagship in-memory computing platform to the Apache Software Foundation with the intention of attracting external developers and growing a viable community around its core technology.
Hazelcast announce their new 3.3.1 release, with JCache support, preview their technology roadmap and discuss their run for the JCP Executive Committee.
In their presentation posted at InfoQ systems and data architects Ben Stopford, Farzad Pezeshkpour and Mark Atwell show how RBS leveraged new technologies in their architectures while facing difficult challenges such as regulation, competition and tighter budgets. They also need to cope with stringent technical challenges, for instance with efficiency and scalability.
The Amazon Web Services (AWS) team announced a set of resources targeting the high performance computing needs of the scientific community. AWS specifically highlights their “spot pricing” market as a way to do cost-effective, massive scale computing in Amazon cloud environment.
Oracle has today released version 3.7 of Coherence, its distributed in-memory data grid. The new product introduces a feature called Elastic Data. According to Cameron Purdy, Vice President of Development for the Coherence product, this allows near memory speed access to data, regardless of storage medium.
Yahoo recently announced and presented a redesign of the core map-reduce architecture for Hadoop to allow for easier upgrades, larger clusters, fast recovery, and to support programming paradigms in addition to Map-Reduce. The new design is quite similar to the open source Mesos cluster management project - both Yahoo and Mesos commented on the differences and opportunities.
The Apache Software Foundation has selected the Object Oriented Data Technology architecture to become one of its Top-Level-Projects (TLP). Originally created by NASA’s Jet Propulsion Laboratory, Pasadena, OODT allows transparent integration of geographically distributed and disparate computing and data resources via metadata middleware.
This month GridGain CEO Nikita Ivanov will be speaking about functional programming at JavaOne in San Francisco. With its 3.0 release, GridGain added a more functional feel to its product by reworking the APIs. InfoQ contacted Mr. Ivanov to get the deeper story about his company's experiences with functional programming.
Amazon has announced the new AWS SDK for Java this March. The aim of the new SDK is to simplify the development of java applications that use the Amazon EC2. The AWS Toolkit for Eclipse automates most of the steps required for the development cycle such as deployment, debugging, instance launching and network access management on the Amazon cluster
GigaSpaces XAP is a distributed application server with an in-memory data grid. The XAP 7.1 release includes a number of themes: an Elastic Middleware Service, enhanced virtualization compatibility, data querying, an updated web-based management application, embedded Spring 3.0, and performance improvements. InfoQ explored this EA release to learn more.
There are two technologies which bring communication into browser-based applications at the moment; Bayeux (aka CometD) and more recently, WebSockets. Will one supersede the other, or are there sufficient differences for both to thrive?
Plura Processing is a SETI-like distributed network harnessing the power of tens of thousands of computers.
Oracle has released Coherence 3.5 with support for tera-scale data grids and a service guardian promoting enhanced cluster health and stability.
In this 3-parts series of articles, David Pallmann explains how to perform grid computations on the Azure cloud computing platform. In Part 1 he presented a design pattern for using Azure for grid computing, while in Part 2 he showed how to develop such an application in C#. In this part he is going to explain how to run this application.
Article: Grid Computing on the Azure Cloud Computing Platform, Part 2: Developing a Grid Application
In this 3-parts series of articles, David Pallmann explains how to perform grid computations on the Azure cloud computing platform. In Part 1 he presented a design pattern for using Azure for grid computing, while in Part 2 he shows how to develop such an application. In Part 3 he is going to run this application.