Category Archives: OpenSpaces

Terracotta ehCache vs. GigaSpaces Cache benchmark

Are you Really using the Fastest and Most Scalable Cache with your Application? We are hearing lately reports from several accounts "discovering" that Terracotta ehcache is not the fastest and most scalable cache out there. GigaSpaces local cache actually performs … Continue reading

Posted in Application Architecture, Application Performance, Benchmarks, Caching, Data Grid, GigaSpaces, Java, JavaSpaces, OpenSpaces | 2 Comments

Possible Impossibility – The Race to Zero Latency

I recently read a book called: "Physics of the Impossible" by the theoretical physicist Michio Kaku. Dr. Kaku lists "Possible Impossibilities" and classifies these into different categories where all these "impossibilities" may happen in the near/distant future. When talking about "zero … Continue reading

Posted in Application Architecture, Application Performance, Benchmarks, Caching, Cloud, Data Grid, Development, Events, GigaSpaces, Java, JavaSpaces, OpenSpaces, sba, space-based architecture | Leave a comment

new and modified best practices

Our best practices wiki is growing rapidly and full with good and useful material. Here are few new best practices added lately: - Finding Partition Load – routing data based on partition load. - Even Data Distribution – simple example explains how to evenly partition … Continue reading

Posted in .Net, Application Architecture, Application Performance, Benchmarks, Caching, Data Grid, Development, GigaSpaces, Java, JavaSpaces, OpenSpaces, Share Nothing Architecture, space-based architecture | Leave a comment

Custom Matching-Two Dimensional Cartesian space Comparison using GigaSpaces

Usually you index and execute queries using primitive fields (long, float, string, etc). The fields may be within the root level of the space object, or embedded within nested objects within the space object. You may construct a query using … Continue reading

Posted in Application Architecture, Application Performance, Benchmarks, Data Grid, Development, GigaSpaces, Java, JavaSpaces, OpenSpaces, sba, space-based architecture | Leave a comment

The Master-Worker Pattern

The Master-Worker Pattern (sometimes called Master-Slave pattern) is used for parallel processing. It follows a simple approach that allows applications to perform simultaneous processing across multiple machines or processes via a Master and multiple Workers. In GigaSpaces XAP, you can … Continue reading

Posted in Application Architecture, Application Performance, Data Grid, Development, Events, GigaSpaces, Java, JavaSpaces, OpenSpaces, sba, SOA, space-based architecture, Spring Framework | Leave a comment