Native workbench that includes notebooks, dashboards, and a common interface for all commands and tasks. This enables data engineers and data scientists to collaborate using familiar tools, languages, and data processing engines.
Qubole is a cloud-native data platform for machine learning, AI, and big data analytics. Qubole on Google Cloud Platform (GCP) provides a first-class user experience through a unified workbench that includes notebooks, dashboards, a native interface for all commands, and built-in tools for easy, secure collaboration.
Qubole’s self-service platform combines the performance, reliability, and scalability of GCP, enabling easier, more collaborative processing of big data workloads on Apache Spark and Hadoop.
Native workbench that includes notebooks, dashboards, and a common interface for all commands and tasks. This enables data engineers and data scientists to collaborate using familiar tools, languages, and data processing engines.
Fast access to Qubole through GCP Marketplace, with automatic account setup, Google Cloud authentication, and simplified user onboarding.
Highly optimized versions of open source engines and frameworks with advanced caching and performance optimizations. Dedicated support and engineering teams specialized by engine.
Automatic upscaling, rebalancing, and aggressive downscaling of clusters with a complete context of the workload, SLA, and priority of each job. Includes intelligent autonomous and policy-based management of regular compute instances or Preemptible VMs.
Fine-grained predefined or custom identity and access management roles to separate compute and data access. Qubole also offers role-based access controls for secure collaboration in notebooks and commands.
Connectors for Google Cloud Storage, Google BigQuery, Oracle, MySQL, Postgres, MongoDB, and more.
Qubole allows you to efficiently manage all major functions of the cluster lifecycle — configure, provision, monitor, scale, optimize, and recover — through automation. Qubole’s built-in financial governance capabilities provide immediate visibility into platform usage costs with advanced tools for budget allocation, chargeback, and monitoring and controlling your cloud spend.
Qubole’s workload-aware autoscaling upscales, downscales, and rebalances clusters with a complete context of the workload, SLA, and priority of each job. Aggressive Cluster Downscaling uses intelligent self-learning algorithms such as Smart Victim Selection, Graceful Downscaling, and Container Packing to balance workloads across active nodes and decommission idle ones without the risk of data loss.
Qubole’s intelligent management of low-cost compute nodes allows organizations to optimize the use of Google’s Preemptible VMs, resulting in drastic cost savings. Qubole provides policy-based automation of Preemptible VM usage to balance performance, cost, and SLA compliance.
Qubole’s Heterogeneous Cluster Configuration for on-demand and Preemptible VMs allows you to pick the most cost-effective combination for your job through automation. Qubole enables you to configure heterogeneous clusters by mixing nodes of multiple instance types, delivering much greater data processing efficiency.
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.
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