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 find it difficult to describe
Visitors are looking for a specific price/features of a product
Visitors come looking for good discounts, to see what's new, and so on
Visitors wish to compare multiple products on the basis of cost/features/reviews
Most e-commerce websites used to be built on custom developed pages, which ran on a SQL database. Although a database provides excellent capabilities to manage your data structurally, it does not provide high speed searches and facets as it does in Solr. In addition to this, 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 a browsing and searching experience. Solr can easily integrate with a database, and provide a high-speed search with real-time indexing. Advanced inbuilt features of Solr, such as suggestions, such as the search, and a spell checker, can effectively help customers gain access to the merchandise they're looking for. Such an instance can easily be integrated with current sites. Faceting can provide interesting filters based on the highest discounts on items, price range, types of merchandise, products from different companies, and so on, which in turn helps to provide a unique shopping experience for end users. Many e-commerce based companies, such as Rakuten.com, DollarDays, and Macy's have acquired distributed Solr-based solutions, preferring these to traditional approaches, so as to provide customers with a better browsing experience.