During this project NoSQL technologies for Hotel IT have been evaluated. It has been determined that among NoSQL technologies, document database fits the best this use-case. Couchbase and MongoDB, the two main documents stores have been evaluated, their similarities and differences have been highlighted. This reveals that document-oriented features were more developed in MongoDB than Couchbase, this has a direct impact on search of reservations functionality. However Couchbase offers a better way to replicate data across two remote data centers. As one of the goals was to provide a powerful search functionality, it has been decided to use MongoDB as a database for this project. A proof of concept has been developed, it enables to search reservations by property code, guest name, check-in date and check-out date using a REST/JSON interface and confirms that MongoDB could work for storing hotel reservations in terms of functionality. Then different experiments have been conducted on this system such as throughput and response time using specific hotel reservation search query and data set. The results we got reached our targets. We also performed a scalability test, using MongoDB sharding functionalities to distribute data across several machines (shards) using different strategies (shard keys) so as to provide configuration recommendations. Our main finding was that it was not necessary to always distribute the database. Then if "sharding" is needed, distributing the data according to the property code will make the database go faster, because queries will be sent directly to the good machine(s) in the cluster and thus avoid "scatter-gather" query. Finally some search optimizations have been proposed, and in particular how an advanced search by names could be implemented with MongoDB. / <p>This thesis is submitted in the framework of a double degree between Compiègne University Of Technology (UTC) and Linköping University (LiU)</p>