Solr vs. ElasticSearch

Question

What are the core architectural differences between these technologies?

Also, what use cases are generally more appropriate for each?

Answer 1

I have created a table of major differences between elasticsearch and Solr and splunk, you can use it as 2016 update:

Answer 2

I only use Elastic-search. Since I found solr is very hard to start. Elastic-search's features:

1. Easy to start, very few setting. Even a newbie can setup a cluster step by step.
2. Simple Restful API which using NoSQL query. And many language libraries for easy accessing.
3. Good document, you can read the book: . There is a web version on official website.

Answer 3

Add an nested document in solr very complex and nested data search also very complex. but Elastic Search easy to add nested document and search

Answer 4

I have been working on both solr and elastic search for .Net applications. The major difference what i have faced is

Elastic search :

• More code and less configuration, however there are api's to change but still is a code change
• for complex types, type within types i.e nested types(wasn't able to achieve in solr)

Solr :

• less code and more configuration and hence less maintenance
• for grouping results during querying(lots of work to achieve in elastic search in short no straight way)

Answer 5

I have use Elasticsearch for 3 years and Solr for about a month, I feel elasticsearch cluster is quite easy to install as compared to Solr installation. Elasticsearch has a pool of help documents with great explanation. One of the use case I was stuck up with Histogram Aggregation which was available in ES however not found in Solr.

Answer 6

I see some of the above answers are now a bit out of date. From my perspective, and I work with both Solr(Cloud and non-Cloud) and ElasticSearch on a daily basis, here are some interesting differences:

• Community: Solr has a bigger, more mature user, dev, and contributor community. ES has a smaller, but active community of users and a growing community of contributors
• Maturity: Solr is more mature, but ES has grown rapidly and I consider it stable
• Performance: hard to judge. I/we have not done direct performance benchmarks. A person at LinkedIn did compare Solr vs. ES vs. Sensei once, but the initial results should be ignored because they used non-expert setup for both Solr and ES.
• Design: People love Solr. The Java API is somewhat verbose, but people like how it's put together. Solr code is unfortunately not always very pretty. Also, ES has sharding, real-time replication, document and routing built-in. While some of this exists in Solr, too, it feels a bit like an after-thought.
• Support: there are companies providing tech and consulting support for both Solr and ElasticSearch. I think the only company that provides support for both is Sematext (disclosure: I'm Sematext founder)
• Scalability: both can be scaled to very large clusters. ES is easier to scale than pre-Solr 4.0 version of Solr, but with Solr 4.0 that's no longer the case.

For more thorough coverage of Solr vs. ElasticSearch topic have a look at http://blog.sematext.com/2012/08/23/solr-vs-elasticsearch-part-1-overview/ . This is the first post in the series of posts from Sematext doing direct and neutral Solr vs. ElasticSearch comparison. Disclosure: I work at Sematext.