Welcome to the SQLstream University Partner Program (UPP). This program is designed to give you the support and resources you need to access non-commercial licenses and internal research and development use of a wide range of SQLstream’s products and knowledgebase. SQLstream, Inc. is dedicated to developing cutting-edge, open technology while supporting the advancement of research through collaborative innovations throughout the Big Data ecosystem.
If you are a recognized university or college looking to expand research into streaming Big Data concepts, the SQLstream University Partner Program offers a non-commercial, royalty-free license to our technology while used within your organization. As a SQLstream University Partner, your undergraduate and graduate scholars have access to the full depth and breadth of real-world streaming data knowledge as shared among other educational institutions and participating enterprise organizations.
The Cornell University Center for Advanced Computing (CAC) is a leader in high-performance computing systems, applications, and data solutions that enable research success.
The Center operates and maintains high-performance computing (HPC) systems and cloud computing services running CentOS, Red Hat Linux, Hadoop, Eucalyptus, and other computing platforms. Storage systems are available at the petabyte scale. CAC staff provides services in architecture design and planning, application porting, tuning and optimization, computer programming, code parallelization, database design, workflow management, Web portal design, data management, and visualization.
The Center’s historic firsts include: first of 5 U.S. supercomputing centers, first IBM SP deployment, first Dell supercomputer deployment, first financial solutions center focused on using high performance computing to manage risk, and first parallel MATLAB cyberinfrastructure utility available on-demand.cac.cornell.edu Case study UPP Press Release
“Too many computing systems producing too many logs too quickly are unmanageble. The SQLstream solution enabled us to analyze log data in real time, identifying patterns indicating imminent and undesirable conditions.” Lucia Walle, CAC