Qubole Customers get 40% better TCO compared to Databricks with same performance and ease of use
Reduce Data Lake Cost by at least 50%
Faster Adoption of Data Lakes
Reduce CAPEX and OPEX by atleast 50% Significantly reduce cloud computing costs with sustainable economics through built-in capabilities such as workload-aware autoscaling, automated lifecycle cluster management, intelligent spot management, and heterogeneous cluster configurations.
Maximize Spot Instance Savings while Minimizing Job Interruptions Allow organizations to optimize the use of Spot instances (AWS or Google), resulting in cost savings of up to 80% on compute costs. Qubole provides policy-based automation of Spot instance management to balance performance, cost, and SLA requirements. Qubole scales underlying compute automatically as needed for bursty data workloads while keeping the cost low
Near-Zero Administration Qubole automates the installation, configuration, and maintenance of clusters, multiple open-source engines, and purpose-built tools for data exploration, ad-hoc analytics, streaming analytics and machine learning. Organizations realize administrator-to-user ratios of 1:200 or higher and near-zero administration experience.
Execute any ML, AI, Streaming or Analytics Use Case To realize the faster adoption of the data lake, you need a platform that is open for multiple use cases and personas. Qubole includes an out-of-the-box workbench and notebooks for data scientists, data engineers, data analysts, and administrators. It supports open source frameworks used by every type of data user including Apache Spark, Presto, Hive/Hadoop, and Airflow.
“Because we let Qubole manage the scaling of our clusters, we also have the ability to specify using spot instances, rather than just everything on demand, and we can tune that. That saves a lot of money.” -Nathan McIntyre, Data Engineer, Ibotta
“The savings from Qubole makes our data engineering team much more productive. Our data engineering team moved away from doing routine maintenance and management work to focusing on serving our customers’ needs and road safety.” -Lei Pan, Director of Engineering, Cloud Infrastructure, Nauto
“We are looking to increase our investment in machine learning-based products multifold, and due to our early partnership with Qubole, we have the data and infrastructure ready to enable that.” -Barkha Saxena, VP Data Science and Analytics, Poshmark
“We were able to scale up quite a lot on Qubole. The reason why is we are able to use Spot instances a lot more with Qubole than with other platforms.” -Dan Peterson, VP of Systems Engineering, Neustar