Hi! I'm the author of <a href="http://solr-vs-elasticsearch.com" rel="nofollow">http://solr-vs-elasticsearch.com</a><p>It's something I threw together in a couple hours, and figured I'd iterate and improve over the next couple days, so please bear with the mistakes.<p>I fixed the more glaring errors (copy field, dynamic fields , Django etc), and will continue to do so as comments come in.
I've been playing with ElasticSearch + Tire[0] over the span of the last week. It's a joy to use. Sunspot + Solr isn't a bad alternative, though.<p>Tire's docs are a bit lacking but it maps more-or-less 1:1 with ElasticSearch, so it's not too bad.<p>Very pleased with the performance ElasticSearch provides. The installation was a bit foreign for me personally (a java service container? openjdk 6 or 7?) but it's lightning quick and very flexible.<p>I chose to go the ElasticSearch route mainly due to my need for Geospatial indexing. Solr does it too, but Foursquare[1] uses ElasticSearch and so that got me interested in learning more. Geo queries are really fast. My last experience with Geo involved GeoDjango and all kinds of obnoxious hacks to PostgreSQL to make it work. With ElasticSearch you tell it to index a point and boom you're off to the races.<p>[0]: <a href="https://github.com/karmi/tire" rel="nofollow">https://github.com/karmi/tire</a><p>[1]: <a href="https://foursquare.com/about/" rel="nofollow">https://foursquare.com/about/</a>
I love both Solr and ElasticSearch but the big missing comparison for me is: are there any books available? Or even comprehensive tutorials beyond the basics? I love ElasticSearch but it was a huge pain getting up-to-speed on everything. Figuring out things like EdgeNGrams (something I already knew how to do in Solr and Lucene) meant digging into the source code. I'm not shy about doing that myself, but giving that advice to a consulting client would be a non-starter. With the explosive growth of ES just in the last year or two, it's really time for someone to start working on a book. Packt, Manning, O'Reilly, any news?
Add geospatial to your comparison chart please. The way in which these implement support varies widely in performance and accuracy. I've yet to find one that actually uses R-Trees. Geohashes seem to be all the rage these days.
I'm not an ElasticSearch expert but it seems that the scenario for "Field copying" would be supported with the multi_field indexing ( <a href="http://www.elasticsearch.org/guide/reference/mapping/multi-field-type.html" rel="nofollow">http://www.elasticsearch.org/guide/reference/mapping/multi-f...</a> )
Good overview - shows you just how powerful these engines are.<p>I can't speak for ElasticSearch but there are a couple things in the Solr list that I'm not sure about.<p><i>"Multiple document types per schema"</i> - You can use dynamic fields so that you don't even need to define your document schema<p><i>"Schema change requires restart"</i> - I think in MultiCore it happens when you swap cores (which is a good way of running solr) [0]<p>[0] <a href="http://stackoverflow.com/questions/10417422/solr-schema-changes-arent-picked-up-unless-solr-is-stopped-for-3-seconds" rel="nofollow">http://stackoverflow.com/questions/10417422/solr-schema-chan...</a>
3rd party integration of ElasticSearch with Django: <a href="http://haystacksearch.org/" rel="nofollow">http://haystacksearch.org/</a>. So I'm not sure why the article says N/A.
both are nice and will do the job without too much pain. I've been running an es cluster for about a year now. I appreciate how easy it is to setup but the documentation is terrible.
es doc should be a cross between rethinkdb and redis. that would make life easier for everybody.
Having played with both, I personally find <a href="http://www.searchify.com/" rel="nofollow">http://www.searchify.com/</a> <i>much</i> better than bost Solr And ElasticSearch. At least based off the search results.