Eliminate data silos and iterate faster. Deploy new use cases in days.
Shared infrastructure for all users. Choose your preferred data processing engines for every workload.
Decouple compute and storage. Optimize performance for big data workloads.
Automation features enable self-service while reducing total spend on cloud infrastructure.
As a cloud-native platform, with a significant headstart on both Hortonworks and Cloudera on the cloud, Qubole achieves 30-40% better query performance for Apache Spark and 20% better query performance for Hive.
To realize the full benefits of the cloud, you need a platform built for the cloud. Unlike legacy on-premises platforms, Qubole’s cloud-native platform provides sophisticated workload-aware autoscaling, automatic cluster start/stop, and heterogeneous cluster configurations that help optimize and reduce infrastructure costs by 50 percent or more.
Cloudera and Hortonworks have significant product overlap, and it is unclear which offerings will survive the merger or if cross-product synergies even exist. Now is the ideal time for customers to switch to a platform like Qubole — a company with a dedicated investment in product stability, cloud technology, and the future of big data.
On-premises Hadoop vendors cannot support the infrastructure demands of advanced analytics and AI/ML. Qubole is an agile, scalable platform that combines structured, semi-structured, and unstructured data for use with your open source big data frameworks of choice.
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.
Free access to Qubole for 30 days to build data pipelines, bring machine learning to production, and analyze any data type from any data source.
See what our Open Data Lake Platform can do for you in 35 minutes.