Jason Search Engine

With fast-growing technologies such as social media, cloud computing, mobile applications, and big data, these are exciting, and challenging, times to be in computing. One of the main challenges facing software architects is handling the massive volume of data consumed and produced by a huge, global user base. In addition, users expect online applications to always be available and responsive. To address the scalability and availability needs of modern web applications, we’ve seen a growing interest in specialized, nonrelational data storage and processing technologies, collectively known as No SQL (Not only SQL ). These systems share a common design pattern of matching storage and processing engines to specific types of data rather than forcing all data into the once-standard relational model.

Specifically, Jason is a scalable, ready-to-deploy enterprise search engine that’s optimized to search large volumes of text-centric data and return results sorted by relevance. For this SaaS please contact us of anytime for more information.

Features:

• Scalable— scales by distributing work (indexing and query processing) to multiple servers in a cluster.
• Optimized for search— is fast and can execute complex queries in subsecond speed, often only tens of milliseconds.
• Large volumes of documents— is designed to deal with indexes containing many millions of documents.
• Text-centric— is optimized for searching natural-language text, like emails, web pages, resumes, PDF documents, and social messages such as tweets or blogs.
• Results sorted by relevance— returns documents in ranked order based on how relevant each document is to the user’s query