Terracotta Inc has released BigMemory 3.7, an off-heap store snap-in for Enterprise Ehcache. BigMemory speeds up applications by keeping data in memory, without the long garbage collection pauses that is common for large JVM heap sizes. New in this version is support for multi-terabyte servers, lower search indexing overhead, and enhanced security.
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.
Recently Couchbase published a comparison of Couchbase and CouchDB to denote the differences and simlarities between the two. This document addresses a common question: "What is the difference between CouchDB and Couchbase?", and what happened to Membase? InfoQ caught up with James Phillips, a Couchbase founder, to discuss the comparison and the merger of the two products Membase and CouchDB.
Mark McGranaghan gave his talk about "High Availability at Heroku" at QCon London 2012. His most important points and take-aways are summarized in this report.
Version 2.0 of Hazelcast, a Java-based caching, clustering and data distribution solution, has recently been released. As part of this, the product is now offered in both commercial Enterprise and free open-source Community Editions.
Oracle fires a new round for the heart of the NoSQL market. This 7.2 release of MySQL Cluster has new features putting it head to head with other NoSQL solutions including REST, memcached wire protocol, NoSQL C++, and standard MySQL interfaces. Oracle boasts 70x speed gains for complex queries using MapReduce like distributed joins. Is the world ready for a MySQL/NoSQL hybrid from Oracle?
VMware releases SQLFire 1.0 a distributed SQL database geared towards high availability and horizontal scalability which offers table replication, table partitioning and parallel execution of queries.
With the release of version 4.0.24, the cache for Caucho's Resin Application Server now provides a memcached interface for both the client and the server. This means that Resin can function as a drop-in replacement for memcached solutions.
The MagLev project has released version 1.0 of their Ruby VM. The Ruby implementation is based on the GemStone/S Smalltalk VM which comes with GemStone's distributed cache, ACID transactions, and persistence system (OODB). InfoQ caught up with Monty Williams of the MagLev project to talk about where MagLev fits on the NoSQL spectrum, and much more.
NoSQL data stores offer alternative data storage options for non-relational data types like document based, object graphs, and key-value pairs. Can a distributed cache be used as a NoSQL store? Greg Luck from Ehcache wrote about the similarities between a distributed cache and a NoSQL data store. InfoQ caught up with him to talk about this use case and its advantages and limitations.
JSR-347 is the data grid specification. This specification came to life with a bit of controversy and confusion. InfoQ got a chance to catch up with Manik Surtani to get his take on JSR 347 and JSR 107 as well as his thoughts on caching, NoSQL, data grids and related topics.
Around January 2011, Memcached became the number one caching solution based on Java developer job demand. Memcached expanded beyond its LAMP roots. InfoQ caught up with Dustin Sallings, the implementer of Spymemcached the leading Java Memcached client, to get his perspective on the rise of Memcached in the Java world.
Second Level Caching is one of the features that is not present out-of-the-box in Entity Framework. In an MSDN article “Second-Level Caching in the Entity Framework and AppFabric” Julie Lerman shows how to implement Second Level Caching with Entity Framework to take advantage of caching services like Microsoft AppFabric.
Distributed caching is the tip of the spear for performance, yet Java does not have a standard API. JSR-107 has gained some notoriety over the years because its old yet not done. Given the increased demand for caching, it seems JSR-107 will finally see the light of day, and be part of Java EE 7. InfoQ caught up with Greg Luck, JSR-107 specification and Ehcache lead developer to discuss.
The new Read-Through and Write-Behind support in AppFabric 1.1 allow developers to improve performance while at the same time reduce the complexity of their applications. This is done by moving the logic for reading from and writing to the database into the caching server itself. Other improvements include lazy-loading of session state information and support for ASP.NET output caching.