These days, Solr and Elsticsearch are two one of the most famous Apache Lucene-based search engine available. These both share many features in common. However, there are some differences between them in functionality, deployment, query language, and scalability.
If you do not have much time and quickly want to understand the differences between them, then it is – The Solr is an entirely open-source search engine. On the other hand, Elasticsearch, though open-source but is still managed by Elastic’s employees. Solr supports text search, while when you want to perform an analytical query, filtering, and grouping, this search engine is the perfect pick for it.
In this article, we are going to discuss in detail about Solr Vs. Elasticsearch which is better.
Let us get started.
Solr Overview
Solr is an open-source search engine built in a Java library, Lucene. It provides you with all of Apache Lucene’s search features in an easy-to-use way.
This search engine has been in the industry for almost a decade. Solr is a proven product and has a broad and robust user community. This search engine offers automatic load balancing, distributed reindexing, failover, and recovery queries.
If this search engine is managed well and correctly, it can become a highly reliable, scalable, fault-tolerant search engine. Do you know which search engine many internet giants like Netflix, Instagram, and Amazon use? Solr. Yes! You read it right. It is because it can index and search multiple websites.
Solr Key Features
- Real-time indexing
- Highlighting
- NoSQL features
- Dynamic clustering
- Multi-array search
- Database integration
- Full-text search
Elasticsearch Overview
Elasticsearch is an open-source, distributed, and RESTFUL search engine. It is built on top of the Apache Lucene library.
This search engine offers full-text search capabilities using an HTTP interface. Its official libraries for the Elasticsearch client are available in Java, PHP, Ruby, Perl, .NET, Javascript, and Python.
Elasticsearch Key Features
- Distributed search
- Grouping and Aggregation
- Analytical Search
- Multi-tenancy
- Scan search
Solr vs. Elasticsearch
- Development and Support
Elasticsearch is entirely commercial. On the other hand, Solr is part of the Apache Software Foundation. Apache is a community-based and open source. Anyone can be a part of the Solr community. On the flip side, even though Elasticsearch is commercial, its code is open source, and developers can use and modify it.
- Configuration
When it comes to configuration, Elasticsearch is exceptionally streamlined. Its distribution package size is a fraction of what Solr offers. Its installation procedure is straightforward and can be configured easily. It comes with a JSON configuration. On the other hand, even though the Solr configuration process is simple, it still has issues like clustering algorithms, documentation, and custom shared collections.
- Indexing
When it comes to indexing, Elasticsearch provides far less control to developers. The Solr offers much more control to its developers incorporating full rebalancing permissions.
- Machine Learning
Elasticsearch uses X-pack for machine learning. It is a commercial plugin that is used with Kibana to provide support for machine learning algorithms. It is a paid add on. On the other hand, Solr provides machine learning support for free. All the members who are part of the community can use machine learning-based ranking models and feature extractions.
- Performance
When it comes to a performance metric, there is no clear winner. Elasticsearch works well with dynamic data, whereas Solr offers the best performance when it handles static data.
And The Winner Is
It is not easy to select the clear winner between these two search engines. It requires an in-depth understanding of the use cases they support, their features, scaling options, and the ease of maintenance they offer. The Solr scores higher when it comes to information retrieval. However, Elasticsearch is better at production and scalability. Solr is the perfect pick for open-source enthusiasts, while Elasticsearch is ideal for the people who work with fluid data.
Solr vs. Elasticsearch, which is better? It isn’t easy to decide and depends entirely on the use cases for which you require a search engine.
In this blog, we have tried to list all the significant differences between Apache Solr and Elasticsearch. However, before settling down for any search engine, ensure to look out at your requirements and, based on that, select the best one for a specific use.