Radius Intelligence Implements Databricks Cloud to Maximize Data Processing Throughput, Speed, and Engineer Productivity
Mar 5 15
Databricks announced that Radius Intelligence selected Databricks Cloud as its preferred big-data processing platform. Radius switched to the real-time Databricks Cloud platform to maximize throughput, speed and engineer productivity to help its customers realize the platform's vision of true targeted marketing. On a daily basis, Radius processes billions of data points from customers and external data sources to help marketers deploy targeted campaigns and predict future marketing and campaign success. The Radius team initially implemented the process of matching and harmonizing their data sets in Hadoop but found the solution hampered IT effectiveness, was too slow to handle increased code maintainability demands and bottlenecked the company's ability to test new solutions. Databricks Cloud was chosen as it is the only solution that can overcome these challenges in a single unified platform by leveraging the power of Apache Spark. Radius was able to fully harness the power of Spark by deploying Databricks Cloud to maintain their Spark infrastructure, and to provide additional critical data analytics components on top of Spark, including: Fully managed Spark clusters in the cloud that help enterprises focus on their data and not operations. An interactive workspace for exploration and visualization so teams can learn, work and collaborate in a single, easy to use environment. An extensible platform that enables organizations to connect their existing data applications with Spark to disseminate the power of big data. By deploying Databricks Cloud, Radius and its customers have enjoyed tangible benefits. For instance, Radius' core data index now takes only a few hours to build, while the same task previously took over a day to complete. Additionally, Radius teams have seen dramatic increases in overall effectiveness and can now work together to test hypotheses in real-time rather than over the course of several days. The combination of Spark's speed and Databricks Cloud's rich set of tools has allowed the Radius team to maximize the throughput and speed of data processing, which enables their engineering teams to acquire new capabilities that were not previously possible with Hadoop on Cloudera or Amazon EMR, such as: Iterate running code in the Databricks Cloud interactive workspace (as opposed to Hadoop's batch model) and receive results in minutes or even seconds. In contrast, doing this with Hadoop's batch model required them to constantly create code, jar it and run it end to end on the server. Visualize results of changes to the core matching technology without having to wait an entire day to receive results. Allow collaboration with multiple teams on larger projects.
Databricks and Intel Collaborate to Optimize Apache Spark-Based Analytics for Intel(R) Architecture
Feb 20 15
Databricks, Inc. announced plans to collaborate with Intel to optimize Spark real-time analytic capabilities for Intel architecture. Enterprises are increasingly developing applications to extract real-time insights from large data sets. The necessity for real-time analytics across Intel architecture is a vital piece of the Big Data puzzle to enable the extraction of prompt, actionable insights from large data sets. As an open source framework that enables stream processing as well as fast queries on large data sets stored on a Hadoop cluster, Apache Spark supports new modes of analytics on big data platforms based on the Apache Hadoop ecosystem.
Skytree Teams Up with Databricks to Enhance Skytree Infinity's Performance with Spark
Nov 4 14
Skytree announced that it is partnering with Databricks. Skytree has been Databricks-certified to work with Apache Spark, enabling enterprises to benefit from best-in-class machine learning for interactive workloads. The Skytree Infinity platform makes it easier for enterprises to inject high value machine learning capabilities into their business processes through a comprehensive REST API layer and pre-built Python and Java SDKs. With the Databricks partnership and Spark certification, Skytree Infinity has increased the platforms' ability to work with interactive data and bring high performance, enterprise grade Machine Learning to Spark.