E-commerce websites are meant to work for different types of users. These users visit the websites for multiple reasons:
Visitors are looking for something specific, but they can't really describe what it is
Visitors are looking for a specific product price/features
Visitors come looking for good discounts, what's new, and so on
Visitors wish to compare multiple products on cost/features/reviews
Most e-commerce websites are used to be built on custom developed pages running on a SQL database. Although a database provides excellent capabilities to manage your data structurally, it does not provide high speed searching and faceting like Solr. In addition to that, it becomes difficult to keep up with the queries for high performance. As the size of data grows, it hampers the overall speed and user experience.
Apache Solr in a distributed scenario provides excellent offerings in terms of browsing and searching experience. Solr can work easily, integrate with the database, and it can provide high speed search with real-time indexing. Advanced in-built features of Solr such as suggestions, a more like this search, and spelling checker can effectively help customer reach the merchandise he/she was looking for. The instance can easily be integrated with the current sites; faceting can provide interesting filters based on highest discount items, price range, type of merchandise, products from different companies, and so on, enabling a unique shopping experience for the end users. Many of the e-commerce based companies such as buy.com, dollardays.com, and macys.com have acquired distributed Solr-based solution over the traditional approach for providing customers with better browsing experience.