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

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

Searchable CouchDB with ElasticSearch

Shay Banon (@kimchy) about ElasticSeach integration with CouchDB:

The CouchDB River allows to automatically index couchdb and make it searchable using the excellent _changes stream couchdb provides. […] On top of that, in case of a failover, the couchdb river will automatically be started on another elasticsearch node, and continue indexing from the last indexed seq.

Full text indexing in the NoSQL space seems to see some interesting solutions.

Update: if you are interested to find out more about CouchDB _changes, you should check the video below:

Original title and link: Searchable CouchDB with ElasticSearch (NoSQL databases © myNoSQL)

via: http://www.elasticsearch.com/blog/2010/09/28/the_river_searchable_couchdb.html


Riak Search and Riak Full Text Indexing

Announced a while back and ☞ not quite here yet, Riak Search is Basho’s solution to the full text indexing problem.

While waiting for the release of Riak Search, I think that you can already start doing full text indexing using one of the existing indexing solutions (Lucene[1], Solr[2], ElasticSearch[3], etc.) and Riak post-commit hooks.

Simply put, all you’ll have to do is to create a Riak post-commit hook that feeds data into your indexing system.

The downside of this solution is that:

  1. you’ll still have to make sure that your indexing system is scalable, elastic, etc.
  2. you’ll not be able to use indexed data directly from Riak mapreduce functions, a feature that will be available through Riak Search.

Anyways, until Riak Search is out, why not having some fun!

Update: Embedded below a presentation on Riak Search providing some more details about this upcoming Basho product:

Update: Looks like the other presentation is not available anymore, so here is another on Riak search:

References


Integrating MongoDB with Solr

Sounds like quite a few NoSQL projects are externalizing the full text indexing to either Lucene or Solr (take for example CouchDB integration with Lucene or Neo4j integration with Lucene and Solr).

Now even if there are some basic ways (see [1] and [2]) to achieve this with MongoDB alone, people are still looking for more scalable solutions as shown by this thread ☞ covering Solr integration with MongoDB. The thread also mentions a couple of existing Ruby or Rails plugins for this integration.

One concern that I’ve expressed about the integration with Lucene alone is that you’ll have to deal with its scalability. Solr is one way to do that automatically. Lately I have heard of a new solution for scalable search: ☞ ElasticSearch which sounds quite interesting (nb: I haven’t yet gone through its docs or played with it, but the creator of the project has a long search/indexing history behind. You can find more details about Elastic Search here[3]).