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Memcached Content on InfoQ


Latest featured content about Memcached

Asynchronous Memcached with a Side of Ketchup and Membase

Topics
Membase,
Memcached,
Couchbase,
Caching,
Distributed Document Oriented Database,
Mono,
Companies,
Distributed Cache,
.NET,
Clustering & Caching,
NoSQL,
Performance & Scalability,
Monospace,
Programming,
Database,
Infrastructure,
Asynchronous Programming

Jason Sirota explains with code samples how to combine caching with asynchronous IO using memcached, Membase and Ketchup in order to maximize the throughput of an application.

News about Memcached

CouchDB versus Couchbase: What are the differences, and what happened to Membase?

Topics
Membase,
CouchDB,
Memcached,
Couchbase,
Companies,
Distributed Document Oriented Database,
Distributed Cache,
Caching,
Clustering & Caching,
NoSQL,
Infrastructure,
Database,
Performance & 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.

MySQL Cluster 7.2 Released with 70x Increased Performance and NoSQL Features

Topics
Memcached,
Distributed Cache,
MySQL,
Caching,
Clustering & Caching,
NoSQL,
Relational Databases,
Oracle,
Database,
Companies,
Performance & Scalability,
Infrastructure

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?

Memcached surpasses EhCache and Coherence in Java Job Demand

Topics
JBoss Cache,
Membase,
JBoss,
Memcache,
Couchbase,
RedHat,
Application Servers,
Ehcache,
Memcached,
Distributed Document Oriented Database,
Companies,
Java,
Distributed Cache,
Caching,
Languages,
Clustering & Caching,
NoSQL,
Programming,
Cloud Computing,
Performance & Scalability,
Infrastructure,
Database,
JCache,
Infinispan,
GemFire,
Resin,
Coherence

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 with Entity Framework

Topics
Memcached,
.NET Framework,
Distributed Cache,
Caching,
Data Access,
Clustering & Caching,
.NET,
Performance & Scalability,
Database,
Infrastructure,
Programming,
AppFabric,
Entity Framework

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.

NoSQL Shake-Up. Membase and CouchOne merge into Couchbase

Topics
CouchDB,
Membase,
Couchbase,
Memcached,
Companies,
Distributed Document Oriented Database,
Distributed Cache,
Caching,
Operations,
NoSQL,
Clustering & Caching,
Infrastructure,
Architecture,
Business,
Performance & Scalability,
Database,
Acquisitions

The shape of the NoSQL landscape is changing. The first big market aggregation took place with the merger of Membase Inc. with CouchOne into Couchbase. InfoQ spoke with James Phillip and Damien Katz about the benefits of the merger and future products.

Four NoSQL Add-ons available for Heroku Users

Topics
CouchDB,
Ruby on Rails,
MongoDB,
Ruby,
Memcached,
Couchbase,
Dynamic Languages,
Distributed Document Oriented Database,
Companies,
Caching,
Distributed Cache,
Heroku,
NoSQL,
Languages,
Clustering & Caching,
PaaS,
Architecture,
Database,
Programming,
Performance & Scalability,
Redis,
Infrastructure,
Cloud Computing

The first four NoSQL datastores are available as Add-ons for the Heroku PaaS (platform-as-a-service) platform. Using the Add-on system that was introduced in October 2009, CouchDB from Cloudant, Membase from NorthScale, MongoDB from MongoHQ and Redis were made available for Heroku users.

7 Lessons Learned at Reddit

Topics
Memcached,
Distributed Cache,
Caching,
Stories & Case Studies,
Scalability,
Clustering & Caching,
Infrastructure,
Architecture,
Performance & Scalability,
Agile

Steve Huffman, co-founder of Reddit, shares the main lessons he learned scaling Reddit from a small web application to a large social website.

Presentations about Memcached

Horizontal Scalability via Transient, Shardable, and Share-Nothing Resources

Topics
CouchDB,
Memcached,
Couchbase,
Erlang,
QCon San Francisco 2009,
Heroku,
Distributed Cache,
Distributed Document Oriented Database,
Caching,
Companies,
QCon,
NoSQL,
Scalability,
Functional Programming,
Clustering & Caching,
PaaS,
Architecture,
RabbitMQ,
Performance & Scalability,
Conferences,
Database,
Cloud Computing,
Programming,
Infrastructure,
Hadoop,
Redis

Adam Wiggins believes that now is the time of horizontal scalability achieved by using resources that are transient, shardable and share nothing with other resources. He gives as example several applications and a language: memcached, CouchDB, Hadoop, Redis, Varnish, RabbitMQ, Erlang, detailing how each one applies those principles.

Evolving the Key/Value Programming Model to a Higher Level

Topics
WebSphere eXtreme Scale,
Distributed Cache,
Websphere,
Caching,
IBM,
Application Servers,
Memcached,
Groovy,
Java,
QCon San Francisco 2009,
Companies,
Dynamic Languages,
Clojure,
Languages,
Data Access,
Clustering & Caching,
QCon,
LISP,
JVM Languages,
Programming,
Conferences,
Performance & Scalability,
Database,
Architecture,
Infrastructure,
Coherence,
Redis

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.

Rockstar Memcaching

Topics
Ruby on Rails,
Ruby,
Memcache,
Memcached,
Dynamic Languages,
Caching,
Distributed Cache,
Clustering & Caching,
Languages,
Data Access,
Scalability,
Architecture,
Programming,
Database,
Performance & Scalability,
Infrastructure,
Rails,
RubyFringe

In this presentation from RubyFringe, Tobias Lütke talks about memcached, the widely used caching solution. Tobias explains how to use it and gives some practical tips on what not to do.