I just published "Considering Datastores" in the "articles" section of my blog, a piece discussing various data storage mechanisms and their strengths and weaknesses compared to each other.
One of the most common topologies of GigaSpaces is a cluster of spaces with an external data source and a mirror service, which persist the data to the data source asynchronously. This is commonly known as write behind. Using this topology removes the bottleneck that the data source can create [...]
This year JavaOne will include really cool lab - PetClinic in the Clouds: Scaling a Classic Enterprise Application. In this Hands-on Lab, participants will take a popular Web application (the Spring PetClinic sample application) and modify it so that it can be deployed on the Amazon EC2 cloud computing infrastructure. [...]
Ultra-Scalable and Blazing-Fast: The Sun Fire x4450-Intel 7460-GigaSpaces XAP Platform – 1.8 million operations/sec!
Introduction Over the past several years highly concurrent applications have faced some serious challenges when trying to scale on multi core machines. GigaSpaces scale-out-application server aims to solve this problem by freeing the user from dealing with the need to handle concurrency while building his distributed application. For the last [...]
A common issue I’m facing recently is how to integrate existing tier-based applications with GigaSpaces persistency service, AKA persistency as a service (Paas) or mirror . The motivation is often a result of the acknowledgment that a standard tier based application fails to scale when facing the database throughput limitation. [...]
With the latest release of GigaSpaces eXtreme Application Platform (XAP) 6.0.2 we've refined the integration with Hibernate, the object/relational persistence and query service. Now the Hibernate integration can be used in two ways; One is to use GigaSpaces as 2nd level distributed cache, replacing the default caching solution that comes [...]