SAN CARLOS, Calif. — March 27, 2012 — As demand for data scientists and experts in Big Data technologies grows, it’s becoming increasingly important for students and educators to learn how to use the cutting edge technologies that are defining the Big Data movement. MarkLogic Corporation, the company powering mission-critical Big Data Applications around the world, today announced the new free MarkLogic® Academic License for students and educators. With the MarkLogic® Academic License, students and faculty can download a free, enterprise version of MarkLogic® 5 server for academic projects. By learning how to leverage technology for Big Data, students will have the skills necessary to unlock additional job opportunities after graduating.
“Students and educators are on the front lines of the next generation work-force,” said Keith Carlson, EVP and COO, MarkLogic. “We’re very excited to see the types of applications that are built with the MarkLogic® Academic License. There are a lot of students around the world that are capable of building remarkable applications, and putting the power of MarkLogic in their hands will lead to some very compelling use cases.”
The MarkLogic Academic License is designed for Big Data research needs and has no data storage restrictions, and can be installed on clusters with hundreds of machines and petabytes of data. The new license follows closely behind the release of MarkLogic® Express, a license that allows developers to download a free version of MarkLogic® and build production applications. With MarkLogic® Express, a developer can take a MarkLogic implementation that leverages a 2 CPU node and up to 40 GB of data live.
The MarkLogic® Academic License is available today at the MarkLogic® Community website. To be eligible for the MarkLogic® Academic License, a user must be a faculty or student member at a university. For more details, please visit MarkLogic® license page.
MarkLogic helps customers create value from complex data faster. Our platform ingests data from any source, creating and refining metadata to support powerful models. Customers use these models for deep search and query, building enterprise applications and bringing unique insights to analytics and machine learning.