An auto-scaling cluster, improved I/O optimization, faster queries and support for hybrid pricing — realize significant cost savings (as much as 50%-60% in total) while accomplishing tasks faster.
Your Hadoop cluster is ready within minutes post signup, letting you focus on building sophisticated data pipelines, running queries, scheduling jobs and monetizing your big data.
Provide your data analysts with an easy to use graphical interface, built-in connectors, and seamless, elastic cloud infrastructure—tools that are so intuitive, anyone can use them.
Use QDS to provision clusters in minutes, scale with demand, and run in an environment that makes it easy to manage and optimize Big Data exploration.
QDS requires no changes to your on-premise infrastructure and gives you the flexibility to work with your data on any platform. Over a dozen QDS connectors support imports and exports for: * On-Premise Sources (via SSH) * Cloud Databases and Sources – MongoDB, RDS, Redshift, PostgresSQL, S3, Omniture, Google Analytics, Vertica, MySQL, and Oracle.
QDS runs on an elastic Hadoop-based cluster so you don’t have to worry about managing nodes, setting up clusters or scaling your infrastructure — QDS does all that for you. Users manage a single-node cluster or a cluster with hundreds of nodes with the same ease of use.
Spot Instances allow users to bid on unused Amazon EC2 capacity and run those instances for as long as their bid exceeds the Spot Price. QDS enables you to realize cost savings of as much as 50% to 60% by supporting the Spot Instance pricing model in addition to the Reserved Instance pricing.
Using auto scaling, QDS saves you money by spinning up users’ clusters only when a job begins, then automatically scaling or contracting clusters based on the workload, and spinning down the servers once the job is done.
S3 storage is secure and reliable, but can be slow without QDS I/O optimization. QDS offers up to 5x faster query execution against data in S3 and 2x faster data writes, compared to Amazon Elastic MapReduce.
The QDS Hadoop engine uses daemons to optimize resource allocation, distribution and management. Using advanced caching and query acceleration techniques, Qubole has demonstrated query speeds of up to five times faster compare to other Cloud-based Hadoop solutions.
QDS comes with a graphical user interface for scheduling jobs, a query editor, a visual query builder, and other tools to make your job easier and more productive. Its award — winning data pipeline creator simplifies setting up sophisticated data ingestion and workflows, including data dependencies.
Based on open Apache technologies, the QDS platform includes “Everything as a Service”. This includes Hive, MapReduce, Pig, Oozie and Sqoop, to provide a complete Big Data service. QDS Python SDK provides tools to create Python applications and to integrate QDS data with other tools.