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



Sphinx: All content tagged as Sphinx in NoSQL databases and polyglot persistence

Fulltext search your CouchDB in Ruby

When having to choose what library to use for full text indexing of CouchDB data for a Ruby application, Taylor Luk looked at from Sphinx, Lucene, Ferret, Xapian and decided to go with Xapian with Xapit . Besides the fact that Xapian with Xapit offers a clean interface and customization of the indexing process, there seem to be quite a few important limitations:

  • Xapit is still under active development
  • You need to trigger Index update manually
  • It doesn’t Incremental index update at the moment

I know some are afraid of managing a Java stack, but in the land of indexing, Lucene, Solr, ElasticSearch, IndexTank are the most powerful tools.

Original title and link: Fulltext search your CouchDB in Ruby (NoSQL database©myNoSQL)


Terrastore and ElasticSearch to Replace MySQL, Memcached and Sphinx

Currently we are using PHP, MySQL, Sphinx, and Memcached to serve up pages so quick. […]

[…] Our (MY) final decision was to use Terrastore. I’m not sure if it is the fastest, but it is fast. The main reason is how easy it is to scale with growth, how well it protects the data and keeps multiple copies always available, and the fast release cycle which means it is always improving.

As a replacement for Sphinx , we have considered many, but have landed on ElasticSearch, which just so happens to have a direct integration with Terrastore. A no-brainer for us to choose ElasticSearch for our search and ranking algorithms.

While each piece is important, sometimes it is also about the combo.

Original title and link: Terrastore and ElasticSearch to Replace MySQL, Memcached and Sphinx (NoSQL databases © myNoSQL)