I’ve been wanting a good comparison between ES and Solr for a while, since the question often comes up, and I don’t have enough Solr experience to address it well. The start of this series looks really promising.
Some things from this post that make ES so great for our use cases:
- Multiple types of documents with different structures (think about indexing posts and comments from a WordPress blog in the same index)
- Pretty much all settings and document mappings can be changed on the fly without restarting the cluster (though it does take some forethought to ensure you can use them all)
- Routing allows limiting a search to a single shard. Particularly useful for faceted search.
[Note: for those of you who don’t have the time or inclination to go through all the technical details, here’s a high-level, up-to-date (2015)Solr vs. Elasticsearch overview]
A good Solr vs. ElasticSearch coverage is long overdue. At Sematext we make good use of our own Search Analytics and pay attention to what people search for. Not surprisingly, lots of people are wondering when to choose Solr and when ElasticSearch, and this SolrCloud vs. ElasticSearch question is something we regularly address in our search consulting engagements.
As the Apache Lucene 4.0 release approaches and with it Solr 4.0 release as well, we thought it would be beneficial to take a deeper look and compare the two leading open source search engines built on top of Lucene – Apache Solr and ElasticSearch. Because the topic is very wide and can go deep, we are publishing our research as…
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