Tesora Updates DBaaS Platform, Focuses on OpenStack Icehouse
Tesora updated its database virtualization engine to provide better performance from its Trove-based database as a service (DBaaS).Tesora, provider of a database-as-a-service (DBaaS) platform on OpenStack, announced the latest release of the Tesora Database Virtualization Engine. Version 1.5 of the Tesora Database Virtualization Engine establishes a new customer performance benchmark, posting an 80-fold increase in capacity while providing reductions in latency. Tesora 1.5 delivers adaptive multitenancy, elastic scale-out and a Web-based intuitive UI with new features that add support for SQL views, a cost-based planner and support for MariaDB. It can be used with OpenStack, Amazon Web Services and other cloud platforms, as well as on-premises. "More and more business is done on the web and our customers find themselves trying to balance the growing demands of complex query processing, high concurrency and instantaneous response times," said Amrith Kumar, CTO of Tesora, in a statement. "At Tesora, we're committed to bringing the benefits of scale out DBaaS simplicity without forcing any customer code changes and making it easy to add database capacity as demand grows." Application developers have to build apps that can handle demands from tens of thousands of impatient users who concurrently request access to customized online content. Such demands put extreme stress on a company's database. Tesora customers such as New York City-based mobile development company Majestyk Apps are already leveraging the Tesora Database Virtualization Engine to get their databases to scale and respond quickly.
Majestyk was hired to develop a consumer-facing social application that increases a user's engagement by adding a custom rating system to their photos. The histogram service shows the popularity of user photographs, with tens of thousands of concurrent users and millions of photographs. A sophisticated algorithm decides what pictures to show to whom. The histogram has to be rendered on demand and reflect the most recent comments and ratings by other users. The complex schema and queries make sharding infeasible. In addition, the demand for near instant access to newly uploaded photographs means that simply caching results is insufficient.