Vespa vs. Elasticsearch vs. Solr – The Ultimate Search Engine Comparison
Search engines are an essential part of any content website today.
It is enabling users to easily find and access the information they need.
Vespa, Elasticsearch, and Solr are 3 of the most popular search engines in the market today, each with its own unique features and capabilities.
In this article, we’ll compare them “head to head” with capabilities, features, and performance so you can make the best decision when choosing one.
Let’s compare those search engines!
| Opensource | Yes – Apache | With limitations | Yes – by Yahoo |
|---|---|---|---|
| Managed options | Searchstax, opensolr | elastic cloud open search | https://cloud.vespa.ai/ |
| Deployment | K8s, HDFS, linux | K8S, single machine | Docker, RPM, K8S, ECS |
| Language/Stack | Java | Java | Java, Python API |
Which one to choose?
Choosing the right search engine depends on a variety of factors, such as the nature of the data, the complexity of the search queries, and the performance requirements. Here are some guidelines to help you decide which search engine to use:
- Solr: Solr is a good choice for text-heavy applications that require complex search queries, such as e-commerce sites, news portals, and enterprise search applications. Solr is highly customizable, supports faceting and grouping, and has a robust ecosystem of plugins and extensions. Solr is also known for its scalability and fault tolerance, making it a good choice for large-scale applications.
- Elasticsearch: Elasticsearch is a popular choice for real-time search applications, such as social media feeds, log analysis, and monitoring systems. Elasticsearch is highly scalable and performs well with large volumes of data. Elasticsearch also supports full-text search and aggregations. Elasticsearch is also known for its ease of use and simple deployment options.
- Vespa: Vespa is a good choice for applications that require real-time search and recommendations, such as news portals, e-commerce sites, and social media platforms. Vespa is highly customizable and supports complex search queries, with built-in support for machine learning models and graph processing. Vespa also offers a powerful query language and supports multi-tenancy, making it a good choice for applications that require high performance and scalability.
Ultimately, the choice of search engine depends on the specific needs and requirements of your application. You should consider factors such as the size and complexity of your data, the types of search queries you need to support, and the performance requirements of your application before making a decision.
To summarize
- Solr is the best solution for “all in one”, although it might feed a bit old-fashioned you’ll get all the useful features ready to work
- Elastic on the other hand is the most convenient of those three, it is composable and has a nice and elegant query language
- Vespa is the future of search engines, if you’re considering incorporating AI it is the best choice out there and it will also provide you with most of the “traditional” search engine capabilities