Vast quantities of digital information are being generated today on a daily basis through social networks, blogs, online communities, news sources, and mobile applications as well as our increasingly sensed surroundings. Tremendous insight can be gained by storing and making such ?Big Data? available for exploration in a wide variety of domains. Likely beneficiaries include business, social sciences, public health, national security, political science, public safety, medicine, and government policy. Researchers exploring these benefits need software to manage and analyze Big Data, and researchers investigating algorithms and programming models for Big Data can benefit tremendously by being provided with shared building blocks to use as a foundation for their efforts.
Over the past 3.5 years we have developed an initial version of AsterixDB, a powerful new Big Data Management System (BDMS) for scalably storing, managing, searching, and analyzing collections of Big Data using clusters of commodity computers. AsterixDB has a layered code base that consists of a scalable runtime platform (Hyracks), a model-neutral framework for parallel query compilation for Big Data (Algebricks), and the end-user-targeted AsterixDB BDMS itself. This NSF project is turning AsterixDB and its internal software stack into robust, supported, open-source resources for use by the Big Data applications and technology research communities. AsterixDB and its components will be helpful in training students in Computer Science and other data-related sciences, at universities everywhere, about Big Data technologies. This is critical for addressing the information explosion being brought to us courtesy of social media and the mobile Web.
