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Qubole Data Service (QDS)

Performing big data analysis has been very hard. Until now. Qubole delivers a more accessible way to perform big data analytics for data stored and growing in your AWS, Google and Microsoft cloud accounts. Our product, Qubole Data Service (QDS), serves as a unified interface for performing the myriad of use cases and workloads that a data driven organization will face ranging from ad hoc analysis, predictive analysis, machine learning, streaming and MapReduce to name a few. Users without software development skills can leverage the QDS workbench through our SmartQuery interface without even knowing how to write a SQL query.

The QDS platform is built with extensibility as a core design principle. Developers may connect their applications to automatically drive queries using a number of QDS’ language SDKs. Data analysts may prefer to compose queries directly for data preparation and ETL workloads, or interact with their BI/visualization tool of choice using one of the QDS ODBC connectors.

QDS Data Engines are fully automated and optimized for the cloud. We are continually evaluating new and innovative open-source tools and engines as they gain customer traction. When new technologies mature, we look to incorporate them into our enterprise analytics framework. All these services are tested to perform at petabyte+ scale with enterprise-level support, governance, and management tools.


Three Ways to Drive Queries With Qubole

Workbench

The QDS Workbench enables data scientists and analysts to drive their ah-hoc workloads through their processing engines of choice using an easy-to-use SQL query composer or SmartQuery builder tool.

Custom Applications

Developers can configure their applications to drive various workloads using a number of common language options.

BI & Virtualization Systems

Drive QDS workload using industry-leading, ODBC compliant BI & Visualization tools, including:

Service Management

  • Monitoring
  • Full Support
  • Persistent logging
  • Persistent debugging

Developer Center

Connecting applications to QDS in order to automatically drive various workloads is made easy through the API and a series of SDKs.
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QDS Workbench

The QDS Workbench is a web interface designed for both SQL-proficient users and business analysts who prefer a visual query builder.
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Policy, Governance & Security Center

QDS is able to leverage all of the encryption and security practices inherent in your environment. Set central system policy for users and groups and set your analysts free to do their work.
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ODBC Connector Library

QDS offers a set of ODBC drivers to connect your BI/Visualization tool of choice.
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  • Cross Engine Metadata Search
  • Engine Autoscaling
  • AWS Spot Pricing Optimizer
  • Policy Manager
  • Cloud Tuned
  • Cluster Lifecycle Management

Unified Control Panel Library

The QDS Unified Control Panel Library consists of a set of optimizations common to all QDS Data Engines that bring data scientist, software engineer and business analyst teams together through one common application. Learn More


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QDS Data Engines


Connect to Persistent Storage and Databases


Persistent Storage

QDS accesses, computes and persists data in our customer's owned and controlled cloud accounts and does not require the data be moved.

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Database Connectors

QDS provides pre-built and tested connectors to import and export data in many 3rd party databases and warehouses.

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QDS Cloud Optimized Processing Engines

Qubole adds additional processing engines, as the market demands, with the same integrated Qubole Data Service features customer have come to expect. To learn more about our current processing engines, please click below

 
 

QDS Doesn’t Sacrifice Functionality for Flexibility. QDS is:

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Enterprise Support

Qubole’s industry-leading technical support makes it easy to get onboard and solve issues quickly through 24/7 live chat and phone support.

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Governed

Policy-based administration lets you broadly deploy self-service analytics with no ongoing IT assistance.

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Collaborative

Use a shared QDS workbench for easy access by all analysts in your organization and ODBC connectors to share results with visualization, business intelligence and data mining/machine learning solutions.

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Intuitive

Users can get started on day one composing SQL queries through our simple, web-based UI. Schedule workflows, manage all your data sources, and leverage usage dashboards to monitor the performance and health of your cluster environment. Additionally, you can programmatically access all tools via SDKs and the REST API.

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Cloud Optimized

Using advanced auto-scaling, you’ll pay only for resources actually used. And, if you’re running on Amazon Web Services, you’ll save a lot of money by automatically incorporating spot instances that can cost up to 90% less than on-demand instances. Cloud storage I/O optimization and faster queries using QDS also reduce costs.

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Petabyte-scale and Beyond

With QDS you can scale to thousand-node clusters with ease. You don’t have to worry about starting or stopping clusters, managing nodes, or scaling your infrastructure up or down — QDS does all the heavy lifting for you automatically.

 
 

Only Qubole Gives You Choice

Qubole is the only vendor that enables the connection of data sources residing on multiple clouds, currently including AWS, Microsoft and Google.

Whether you are looking to avoid long term vendor lock in or to simply gain better flexibility, Qubole gives you choices.

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Microsoft Azure

  • Big Data Solutions: Hive and MapReduce
  • Data Sources and Connectors: Azure Storage, ODBC, JDBC, Oracle, MySQL, Vertica, Google Analytics, Omniture, PostgreSQL, MongoDB, SQL Server
  • Tools: Workflow scheduler and Sqoop for import/export of data
  • Development Languages: Java, Python, R, Cascading, and SQL
  • Interfaces: SDKs, REST API, and Web-Based UI
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Amazon Web Services

  • Big Data Solutions: Hive, Spark, Presto, MapReduce, Pig, and HBase
  • Data Sources and Connectors: Amazon S3, ODBC, JDBC, Amazon Redshift, Amazon DynamoDB and Amazon Kinesis, Amazon RDS, Oracle, MySQL, Vertica, Google Analytics, Omniture, PostgreSQL, MongoDB, SQL Server
  • Tools: Workflow scheduler and Sqoop for import/export of data
  • Development Languages: Java, Python, R, Scala, Cascading, and SQL
  • Interfaces: SDKs, REST API, Web-Based UI, and Spark Notebook
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Google Compute Engine

  • Big Data Solutions: Hive and MapReduce
  • Data Sources and Connectors: Google Cloud Storage, ODBC, JDBC, and Google BigQuery, Oracle, MySQL, Vertica, Google Analytics, Omniture, PostgreSQL, MongoDB, SQL Server
  • Tools: Workflow scheduler and Sqoop for import/export of data
  • Development Languages: Java, Python, R, Cascading, and SQL
  • Interfaces: SDKs, REST API, and Web-Based UI