Elasticsearch vs Solr
There are always many reasons behind adopting one technology over another one. In case of Elasticsearch and Solr choose your preferable and best technology. From an operational management perspective: Elasticsearch is like Windows, whereas Solr is like Linux.
Solr can be customized on a large scale to fulfill your needs, but deployment and management require more resources and involvement than Elasticsearch. Whereas Elasticsearch can be easily deployed, manage, and monitor with the help of well-designed user interface (Kibana) that allows data visualization and exploration. Although there are some other differences between them but they are also very much similar to each other. So, choose the best search engine based on given differences.
What is Elasticsearch?
Elasticsearch is a NoSQL database that is used to store data in document form. Many well-known companies, such as – Accenture, Linkedin, and OpenStack use Elasticsearch. It is an open-source search engine developed in Java. It is built on top of Apache Lucene. Elasticsearch is a real-time analysis engine designed for storing logs. It is a schema-less data store used to manage NoSQL data.
What is Solr?
Apache Solr is a Java search server that enables you to easily create a search engine, which searches databases, files, and websites. Many well-known companies such as – Amazon, Netflix, Instagram, and eBay use Apache Solr. It is reliable, fault-tolerant, and scalable search platform that allows to manage, distribute, and scale indexes for large scale application. Apache Solr is also written in Java.
Difference between Elasticsearch and Solr
There are some differences between Elasticsearch and Solr are listed below:
| Elasticsearch | Solr |
|---|---|
| Elasticsearch requires less involvement and resource to deploy and manage it. | Deployment and management of Solr require more effort and resources than Elasticsearch. |
| Elasticsearch has a single community, i.e., Elastic company itself. | Solr has large community support and Apache Software Foundation. |
| It offers a sophisticated and flexible aggregation engine. | It offers a powerful streaming aggregation engine. |
| Elasticsearch is dynamic. It can move shards around a cluster when a certain action happens, such as join or remove a new node from the cluster. | Solr is a bit static. For example – Solr does not do anything itself whenever a cluster joins or leaves the cluster. |
| Many well-known companies, like Accenture, Linkedin, and OpenStack uses it. | Companies like Amazon, Netflix, and Instagram choose Solr. |
| In elasticsearch, multi-tenancy is easier to set up. | In Solr, multi-tenancy is not as much as easier to set up. |
| Elasticsearch provides restrictive plugin architecture. It does not support plugins in a hosted environment. | Apache Solr provides excellent pluggable architecture. It can easily develop and integrate plugins. |
| Elasticsearch is easy to set up and scale. It has API for monitoring and state evolution. | It is difficult to manage as it does not have API for easy monitoring and state evolution. |
Below are some common features that are provided by both Elasticsearch and Solr, such as:
- Replicating
- JAVA and REST API
- Geospatial search
- Faceting
- Highlighting