- Catalog size: Size of catalog in your store.
- Indexing: Search engine capacity to handle a real time search.
- Memory: Server also matters for search engines. Because it requires memory to perform the operation.
Elastic search:
- Elasticsearch is currently at the top position among all the search engines. Elasticsearch has changed the performance limitations. It’s performance and relevance is much higher than all other search engines.
- Elasticsearch also quickly updates the data and it’s very important with real-time indexing.
- When the size of the database increases, it’s difficult to work with it but elastic search also scales up accordingly and it doesn’t impact the search result.
- When you have a large catalog of approximately 60k+ then only you can feel the actual performance impact of elastic search more than the other search engines.
- Elasticsearch also consumes more memory so, your server should be with high configuration.
Solr:
- Solr stands at the second rank on the trending chart of search engines. It has its separate benefits from other search engines. If you want the functionality that your search engine can read the rich content like text, pdf documents then you must prefer the Solr search engine.
- Solr stands at different positions because of its performance and features.
- Solr has very great capabilities for faceted search.
- This search engine works best for the static data which are not frequently updating.
Sphinx:
- The next search engine on my list is Sphinx. Sphinx is a very popular and experienced search engine. This search engine has powerful capabilities for the layered navigations due to its expertise and experiences.
- Sphinx search supports the high scalability but not as compared to the elastic search.
- Sphinx search consumes very less memory than other search engines. When your server is not with the high configuration then you must prefer this search engine.
Sphinx Search vs Elasticsearch
The main difference between Spinx search vs elasticsearch is— Sphinx Search needs managed schema files for defining data types, fields, and index structure whereas Elasticsearch doesn’t need index schema to index data and assign fields types. Sphinx is considered an open-source full-text search engine, whereas Elasticsearch is a tool in the “Search as a Service” category. I hope you got a good understanding of the different kinds of Search Engines. Let me know your thoughts in the comment section. And if you have any queries with this blog I will be happy to solve that. Thanks and cheers … 🙂FAQs
You can choose Elasticsearch or Solr as both are leading search engines. Elasticsearch is faster and easier to use. Though it is heavier than Solr, the performance difference is worth it. On the other hand, Solr has more features and is better suited for complex queries.
No, Elasticsearch is not based on Solr. Both Elasticsearch and Solr are based on the same Java library Lucene and have several similar core features. But Solr is more focused on text-based queries and Elasticsearch works towards analytical queries. Their architecture and community support also vastly differ.
Yes, Amazon uses Solr. Amazon’s CloudSearch service is based on Solr to support full-text searches. It forms the search engine’s functionality by indexing and ranking search results. Though Amazon also uses other search engines, CloudSearch and in turn Solr forms an integral part of all Amazon apps.
Yes, Elasticsearch is the best search engine. Though other search engines are widely used, Elasticsearch’s speed, community support, flexibility, and scalability makes it popular. The search engine can index data within a second, and scale to multiple searches to accommodate petabytes of data. Elasticsearch is best suited for use cases where data updates continually.
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