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Qubole Runs An On-Demand Hadoop In The Cloud SaaS

A conceptual technical diagram illustrating the AWS and Google Cloud Interconnect partnership. It shows jigsaw puzzle pieces of AWS, Azure, Google Cloud, and Oracle, connected by a dedicated network pipe. Accompanying news headlines reference cloud competition and regulatory scrutiny. A pie chart shows cloud market share. Gauges track multicloud spend optimization.
Connecting Rivals: The AWS and Google Cloud agreement establishes a direct, private link between their networks, bypassing the public internet, but analysts suggest the move is more about defining multicloud networking standards than pure customer ease. (Visual: A representation of cloud interoperability versus market control.)
Company Qubole
Address 1032 Elwell Ct, Suite 109 Palo Alto, CA 94303, USA
Founders Ashish Thusoo & Joydeep Sen Sarma
Founded June 2012
Funding $ 1 million
Employees 4
Website www.Qubole.com
Rating 5 bits

 

Qubole runs an on-demand Hadoop in the clouds service platform. It is a managed version of Hive on the Amazon Web Service platform and it was developed by two key players of the team that developed the Hadoop query language Hive. Furthermore, Ashish Thusoo and Joydeep Sen Sarma both worked at Facebook from 2007 2011 and held senior data infrastructure positions.

Hive is a data warehouse for Hadoop and it uses an SQL-like language called HiveQL (Hive Query Language). It can easily summarize data, offers ad-hoc queries and other analysis of big data. Qubole is optimized to run on cloud-based resources and it can run queries five times faster than traditional Hadoop jobs in the cloud. Users can change the types of instances a job is running on if the situation changes. The auto-scaling platform may switch to High-memory Quadruple Extra Large instances if a memory-intensive job is needed. Default the Amazon EC2s High-Memory Extra Large is used.

Qubole users the Open Database Connectivity (ODBC) technology developed by Simba to give users real-time, standard SQL and HiveQL access directly to their Big Data. Users can work with unstructured or structured data directly in the cloud and Qubole takes care of the normally complex tasks of storing and managing the data. Using common Business Intelligence applications users get fast, easy path to analysis and business insights from their data. Qubole takes care of correctly spinning up clusters and automatically optimizes performance.

Although the data is easily stored and accessible for users, Qubole still targets rather experienced data scientists, ETL engineers and analysis that are familiar with writing SQL queries and creating data pipelines. Although using the Integrated Data Workflow Engine Qubole provides the necessary mechanisms to make it as simple as possible. With Qubole users can import data, build data pipelines and export the data again to a set of various sources. As it is a Software-as-a-Service company, this can all be done via the browser.

Qubole is an interesting player in the field of cloud-based Hadoop solutions, but it is by far the only player in the market. Mortar Data is a well-known competitor for example. But they have an advantage that two members who were part of the development of Apache Hive developed Qubole. They are located in both Silicon Valley as Bangalore. In 2012 they managed to secure angel funding of about $ 1 million and they will use this to hire new engineers and to keep growing. It is a promising start-up, but they will need to grow a lot in the coming years to live up to that. We therefore give them a 5 bits rating.

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