ALL COVERED TOPICS

NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter

NAVIGATE MAIN CATEGORIES

Close

MongoDB, memcached, EHCache: Compared as Distributed L2 Caches

As can be seen, whether the off-host process that manages the cache-data is MongoD or MemcacheD or Terracotta-Server, architecturally they all look equivalent - i.e. a pure-L2 with no-L1 - so that all data needs to be retrieved from over the network and then massaged into a POJO for consumption by the application.

MongoDB, memcached, EHCache compared

When speaking about caching systems, I’d also include criteria like:

  • warm up strategy
  • locking strategy
  • single-machine memory spill strategy

Original title and link: MongoDB, memcached, EHCache: Compared as Distributed L2 Caches (NoSQL databases © myNoSQL)

via: http://javamuse.blogspot.com/2011/03/nosql-document-based-or-distributed.html