The Qubole Data Service is built for the cloud; with available services in AWS, Azure, and Oracle Cloud.
No need to manage clusters. Get instant access to Hadoop, Hive, Spark, Presto, and more at the push of a query.
Security for the cloud. Qubole embraces different cloud infrastructures with enterprise compliance (HIPAA, PCI, SOC 2) attestations.
Common user interfaces for developing Hadoop, Spark, Hive, and Presto. Providing each data team self-service access to the data lake
Integrate with technologies from the entire Big Data ecosystem (Apache Kafka, Ranger, HBase, Arrow, H2O, Superset, and many more).
Built-in scheduler, to easily build and manage production data pipelines.
Qubole offers a full set of REST application programming interfaces (APIs) to manage all platform functions from infrastructure to user management
Qubole command APIs to directly submit queries and retrieve results of Hive, Spark, and Presto commands.
Metastore caching for quick discoverability of your datalake, with secure encryption at rest.
Shared metadata caching for to reduce resource inefficiency and improve performance with multiple users querying.
Engine-level caching with Rubix, an open-source technology developed by Qubole, for improving the performance of Presto and Spark workloads
Big data clusters built with workload aware auto-scaling, aggressive down scaling, and optimizations to leverage AWS Spot Instances
Built for petabyte scale with cloud computing. Save and contain costs as you scale workloads, without manual intervention or tuning.
Qubole Hive Metastore allows you to easily create tables and query structured and unstructured data in seconds.
Run federated queries across multiple data sources (NoSQL databases, Data Warehouses, and more) with Qubole Presto.
Use your favorite interface with Qubole SQL engines. Whether it is Analyze Workbench, Notebooks, or connecting your favorite BI tool.
Train. Fast, self-service access to compute allows for rapid model training. Making selecting the right ML model, a quick and iterative process.
Deploy. Whether running batch or real-time ML operations, Qubole is built scale up to petabytes of data, and manage production pipelines.
Live stats collection on Table performance for optimizing production workloads and datasets
Query any file format (JSON, Avro, Parquet, ORC, etc) with any engine. Qubole allows self-service access to analyze cloud storage.
Integrate with your Data Warehouses, RDS, or Data Marts to enable read/write access to Qubole engines
Big data engines (Hadoop, Spark, Presto) built for faster query performance with cloud object stores
Calling all London-based data engineers! Join us for "The Qubole Cricket Challenge" series starting 5 June at Code… twitter.com/i/web/status/11320…
Learn how to create a go to market strategy for a new product category on the @MMEnginepodcast with @BernieBorges… twitter.com/i/web/status/11320…