Natively designed for AWS and tightly integrated with its storage, compute, security and other key architectural elements, QDS on AWS is the best Autonomous Data Platform for any organization implementing big-data projects on Amazon Web Services.

AWS

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Key features and capabilities

Native AWS

Natively designed for AWS

  • Builds upon AWS’s strengths
    • Separation of Compute (EC2) and Storage (S3) for efficient, unlimited scaling
    • End-to-end security (Encryption, IAM roles)
  • Integrates with all major data sources through dedicated connectors
    • Amazon Redshift, Amazon DynamoDB and Amazon Kinesis, Amazon RDS, Oracle, MySQL, Vertica, Google Analytics, Omniture, PostgreSQL, MongoDB, SQL Server

cost effective

Cost effective

  • Uses elastic resources effectively with Workload Aware Auto-Scaling, Spot Shopper and other Cloud Agents

turnkey AWS

Turnkey big-data solution for AWS

  • Eliminates unnecessary steps in the configuration of clusters
  • AWS-optimized Cloud Agents minimize need for manual operations in the set up, scaling of clusters and intelligent use of Spot instances
  • Works with existing customer AWS account. No need to migrate data

AWS optimized

AWS-optimized Engines

Hadoop 1 & 2

Hive, Spark

Presto

Airflow

Pig

deployment flexibility

Deployment flexibility

AWS VPCs

Private Qubole

Architecture

The Qubole Application Tier orchestrates resources on the customer’s AWS account using customer-provided and revocable IAM roles. Meta-data describing the data on S3 is stored in the Hive Metastore in the Qubole tier or, if required, on the customer’s account. Workload requests are submitted by users via a web-based Workbench or via Spark Notebooks, by external applications via REST APIs, and by third party Business Intelligence products via ODBC/JDBC drivers. Query results are cached locally by Qubole for future re-use to minimize use of compute resources.

Architecture