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Clustering & Caching Content on InfoQ


Latest featured content about Clustering & Caching

Attila Szegedi on JVM and GC Performance Tuning at Twitter

Topics
Dynamic Languages,
NoSQL,
Open Source,
Compilers,
JRuby,
Asynchronous Architecture,
Clustering & Caching,
Java,
Database Design,
Performance & Scalability

Attila Szegedi talks about performance tuning Java and Scala programs at Twitter: how to approach GC problems, the importance of asynchronous I/O, when to use MySQL/Cassandra/Redis, and much more.

News about Clustering & Caching

VMware Releases SQLFire 1.0

Topics
Clustering & Caching,
Java,
Persistence,
Data Access,
Performance & Scalability

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.

Distributed Cache as a NoSQL Data Store?

Topics
NoSQL,
Clustering & Caching,
Java,
Big Data,
Data Access

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.

Articles about Clustering & Caching

Concurrency Controls in Data Replication

Topics
Clustering & Caching,
Architecture,
Database Design

Learn about leading concurrency control mechanisms used for data replication in distributed environments, comparing synchronous and asynchronous implementations with/without locking - techniques used by Oracle RAC, TimesTen, and GigaSpaces and NoSQL databases. Explore tradeoffs among performance, consistency, deadlocks, and conflicting updates in the context of a sample distributed application.

Infinispan's GridFileSystem - An In-Memory Grid File System

Topics
Clustering & Caching,
Java,
Architecture

Infinispan is an open source data grid platform that makes use of distributing state across nodes in a cluster. GridFileSystem is a new, experimental API that exposes an Infinispan-backed data grid as a file system. In this article, authors discuss distributed mode of Infinispan and how GridFS framework manages data caching by chunking up data using a new streaming API and storing them in a grid.

Presentations about Clustering & Caching

Scaling Australia's Most Popular Online News Sites with Ehcache

Topics
Clustering & Caching,
Java,
Performance & Scalability

Matthias Matook and Ari Zilka share the real-world experience of implementing Enterprise Ehcache at Australia's most visited online news sites. The talk will focus on the challenges and technical solutions to deal with massive page hits, high concurrency and how to achieve linear scalability without additional hardware.

Evolving the Key/Value Programming Model to a Higher Level

Topics
Java,
Clustering & Caching,
Data Access,
Architecture

In this presentation from QCon San Francisco 2009, Billy Newport discusses the ways that developers interact with key/value (KV) stores such as memcached and WebSphere eXtreme Scale, entity vs column-oriented approaches, synchronous and asynchronous operations, large data sets, using a DBMS as a column store, collocating closures and data, and features that could be added to increase scalability.

Interviews about Clustering & Caching

JSR 107, JSR 347, Infinispan, NoSQL, Hot Rod, Memcached, CDI and Beyond

Topics
Cloud Computing,
Clustering & Caching,
Java

InfoQ catches up with Manik Surtani to discuss JSR 347, data grids and Inifinispan. Manik dicusses overlap with NoSQL and support for Memcached and HotRod wire protocol as well.

Costin Leau on Spring Data, Spring Hadoop and Data Grid Patterns

Topics
NoSQL,
Data Access,
Clustering & Caching,
Big Data,
Database Design,
Persistence,
Performance & Scalability,
Architecture

In this interview recorded at JavaOne 2011 Conference, Spring Hadoop project lead Costin Leau talks about the current state and upcoming features of Spring Data and Spring Hadoop projects. He also talks about the Caching and Data Grid architecture patterns.