Open Data Lake Platform

An open and secure multi-cloud data lake platform for machine learning, streaming analytics, data exploration and ad-hoc analytics.

No other platform radically simplifies data management, data engineering and run-time services like Qubole. Qubole enables reliable, secure data access and collaboration among users while reducing time to value, improving productivity and lowering cloud data lake costs from day one.

Our Unique Advantages

Open, Simple, Secure

Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies.

Fast Data Lake Adoption at Scale

Qubole provides 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, TensorFlow, and Airflow.

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.

Reduce Data Lake Cost by 50%

Qubole’s Workload-aware autoscaling and real-time spot buying drives down compute costs dramatically. Pre-configured financial governance policies and built-in optimization lower data lake cloud computing costs continuously while providing administrator overrides to accommodate special needs.

Qubole is trusted by customers all over the world with getting their data analytics on the cloud right.

Why Open Data Lakes are defining data-driven organizations?

Watch Qubole co-founder Ashish Thusoo discuss the analytics and machine learning use cases that are driving the demand for open data lakes