Cloudant today announced that its cloud database service has been enhanced with integrated, full-text indexing and search powered by Apache Lucene. Using Cloudant “Search 2.0,” developers can quickly and easily enhance their mobile and Web apps with high-performance indexing and analysis of textual documents. It is ideal for developers of online education and research apps, sentiment analysis, or any application that needs to provide fast, cost-effective storage and analysis of large volumes of text data.

Cloudant Search 2.0 provides developers with the familiarity of Lucene, the most popular open-source search library. Unlike other cloud databases, text search is tightly coupled with the Cloudant database, providing unified API access, horizontal scaling, and a single REST endpoint for all application data, including text documents.

In addition, Cloudant’s Search 2.0 uses a system based upon Cloudant’s incremental indexing engine in order to index data in near real time. It also provides a simple, scalable and fast search engine that can process large volumes of data, including high-dimensional data, or concurrent queries.

“Search 2.0 enables the types of text analytics that just aren’t possible with the limited in-database search capabilities of SQL or other search systems,” said Mike Miller, co-founder and chief scientist at Cloudant. “I can’t think of any application out there that wouldn’t benefit from better search. By drawing on the speed and simplicity of Lucene, we are able to provide developers with an easy, familiar way to do that for large amounts of application data that will perform at-scale for massive amounts of users.”

Cloudant Search 2.0 includes support for Lucene’s on-disk index file format, which allows database indexes to be built, maintained and searched very fast for higher overall performance. This format also requires less storage space, therefore lowering overall storage costs. It allows developers to enhance applications with several features:
• Ranked searching – Search results can be ordered by relevance or by custom sort fields
• Powerful query types – Including phrase queries, wildcard queries, proximity queries, range queries and more
• Bookmarking – Paginate results in the style of popular Web search engines
• Fielded searching – Search by specific JSON fields within text documents, including title, author, contents and more   
• Multiple-index searching with merged results – Results from searches based on different Lucene indexes can be logically combined
• Simultaneous update and searching – Leveraging the same incremental indexing engine that is used to index data, it is now used to build search indexes to speed queries and provide transactional control

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