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

Riak: Entropy detection, correction, and conflict resolution

John Daily covers Riak’s mechanisms for bringing data in sync across the nodes:

Riak’s overarching design goal is simple: be maximally available. […] In order to make sure your data can survive server failures, Riak retains multiple copies (replicas) and allows lock-free, uncoordinated updates. […] This then open ups the possibility that data will be out of sync across a cluster. Riak manages this issue in three distinct stages: entropy detection, correction, and conflict resolution.

You’ll read pitches from products promising both maximal availability and no out-of-date data. Those are just that promises.

Original title and link: Riak: Entropy detection, correction, and conflict resolution (NoSQL database©myNoSQL)

via: https://basho.com/entropy-in-riak/