Creators of Facebook’s Big Data infrastructure and Apache Hive have leveraged their experience to deliver Qubole Data Service (QDS) – a cloud Big Data service offering the same advanced capabilities used by Big Data savvy organizations.
Minimize operational interaction and provide your data analysts with an easy to use graphical interface, built-in connectors, and seamless, elastic cloud infrastructure.
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.
An auto-scaling cluster, improved I/O optimization, faster queries and support for hybrid pricing - realize cost savings of as much as 50%-60% in total, while accomplishing tasks faster.
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 that you don’t have to worry about managing nodes, setting up clusters or scaling your infrastructure – QDS takes care of this work for you. Users have the ability to 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 makes it easy 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 is started, then automatically scales or contracts them based on the workload, and spins the servers down 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 than Amazon Elastic MapReduce.
The QDS Hadoop engine makes full use of daemons to optimize resource allocation, distribution and management. Using advanced caching and query acceleration techniques, Qubole has demonstrated query speeds up to five times faster than other Cloud-based Hadoop solutions.
QDS comes with a graphical user interface for scheduling jobs, a query editor, a visual query builder and other ways to make your job easier and more productive. Its award winning data pipeline creator makes it simple to set up sophisticated data ingestion and workflows, including data dependencies.
Based on open Apache technologies, the QDS platform includes “Everything as a Service”…Hive, MapReduce, Pig, Oozie and Sqoop…to provide a complete Big Data service. The QDS Python SDK provides tools to create Python applications and to integrate QDS data with other tools.
Prakash Janakiraman, Co-Founder and VP Engineering
Systems via a Flume that writes data out to Amazon S3. From there, we use a data processing pipeline hosted by Qubole to process and aggregate statistics to Hive (computing)tables and to an AWS Redshift based data warehouse
Yali Sassoon, Co-founder
Qubole is a significantly more polished product than EMR. Data scientists can explore their data in S3, create tables and query those tables all via an easy-to-use web UI
Joris Spermon, VP Tech & Development
Qubole’s fantastic support has been key in our successful deployment. They continue to deliver of new features and revisit the ones that we ask for
Marc Rossen, Sr. Director Data and Analytics
Our goal at MediaMath was to take our existing industry leading infrastructure to the next level handling new complex analytics tasks. Qubole has helped us enable this goal with minimal risk.
Nicholas Andonakis, Senior Product Analyst
Instead of worrying about provisioning clusters of machines or job flows or whatever, Qubole lets you focus on your data and your queries … The Qubole guys have been extremely helpful!
Derrick Harris, Senior Writer
The service spins up users’ clusters only when a job is started, then automatically scales or contracts them based on the workload, and spins the servers down once the job is done.
Senior Director, Game Dev Ops and Analytics
Qubole’s Hadoop and Hive interfaces are vastly superior to the default CLIs, which scare business analysts and hinder meaningful analyses of the gaming logs that we collect. With Qubole, business analysts are self-sufficient in using a Big Data platform to meet their advanced analytic needs.
Online Gaming Company
Geoff Domoracki, Founder and CEO
top-performing technologies in the data industry are definitely taking aim at democratizing data tools and bringing the power of data to smaller businesses. This is a major change in the data industry, and Qubole Data Service is a great example
I’m very happy to be using Qubole in production. Qubole has saved me a lot of time, effort, and trouble in getting my data processing pipelines up and running. My data pipelines process Appnexus data in Amazon S3 which is then stored in Vertica. The engineering team understands the complexities and provided awesome support!
Real-time Ads Retargeting Startup
Derrick Harris, Senior Writer
There’s a whole world of web companies, SMBs and other non-Facebooks or Yahoos that will want to use Hadoop but not want to run it in-house…offering a cloud service makes it easier for these users to get started with the platform and for Qubole to keep improving.
Christian Prokopp, Contributor
Qubole offers a big data ETL and exploration service through auto-scaling Hadoop clusters with a web user interface for data exploration and integration with various data sources. The service can do (nearly) everything EMR can do, and it goes further
Big Data Republic
George Chow, CTO
Simba knows Big Data access. Qubole knows Big Data. Qubole’s founders authored Apache Hive, built key parts of the Hadoop eco-system and brought Apache HBase to Facebook
Paul Lilford, Channel Director
“The integration of Tableau and Qubole makes it faster and easier for our customers to operationalize Big Data…lowers the resource barriers to deriving the benefits of Big Data because customers can deploy our joint solution seamlessly and cost effectively.”
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