Once upon a time, we were happy with search engines that could retrieve textual documents. Today, we want to search through multiple and heterogeneous data sets of any kind, including images, audio/video, highly structured as well as free-form material. Also, we want our search results to be documents, paragraphs, audio segments, as well as named entities such as persons or companies. Spinque software is designed to get all this out of your own data.
A search engine might search a company's intranet, its product catalogue and the logs from the helpdesk. Each of these sources are regarded as different data sets. On the intranet it is likely to have documents with metadata such as a 'created/modified' date and perhaps an author. A product catalogue contains a list of products, associated categories, prices, and perhaps descriptions. A helpdesk log may have date of the telephone call, description of the incident, and proposed solution.
Spinque can provide real-time search for meta-data sets of more than a 100GB on a single server. To put this in perspective, the total size of the whole English Wikipedia is about 30GB.
Additional factors contribute to determine the actual responsiveness of search solutions created on top of your data: the complexity of the search strategies defined, the hardware resources available.