Fastest path to value from big data in the cloud
Save time and money on setup and management of your big data platform
Automatically scale capacity quickly based on your workloads
“I am very happy with Qubole! Our goal at MediaMath was to take our existing industry-leading infrastructure to the next level handling new complex analytics tasks. Qubole has helped us achieve this goal with minimal risk. ” - Rene Englehardt, VP Analytics, MediaMath
“Qubole helped prevent us from making bad decisions that cost the business tens or hundreds of thousands of dollars.” - Robert Barclay, VP of Data and Analytics, Return Path
“Qubole gave us the usability and scalability we need to drive insights from adoption of big data across our entire enterprise. Making our business users self-sufficient got us where we wanted to be.” - Adam Rose, Head of Engineering, Adobe Advertising Cloud
Reduce cloud costs by 50% or more with capabilities such as workload-aware autoscaling, automatic cluster start/stop, and heterogeneous cluster configurations, among others.
Achieve 30-40% better query performance for Apache Spark and 20% better query performance for Hive with Qubole’s optimized cluster startup and shutdown times.
Qubole automates the installation, configuration, and maintenance of clusters, multiple open source engines, and purpose-built tools for data engineers, data scientists, and data analysts. This is how Qubole delivers administrator-to-user ratios of 1:200 or higher. See how Qubole helps Malaysian Airlines drive profitability.
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Run ad hoc analytics combining unstructured, semi-structured, and structured data with native Presto clusters and BI tools like Microsoft Power BI. All with the same performance, auto-scaling, and optimizations available to any other open source engine running on Qubole..
Work smarter with native Apache Spark notebooks, notebook sharing with Access Control Lists, offline viewing, notebook refresh scheduling, auto-saving to cloud storage, dashboards, and support for Apache Airflow for built-in scheduling and workflows.