Headquartered in Silicon Valley, QuboleOpens a new window is among a few Big-Data-Analytics-as-a-Service companies that have gained a firm foothold in the data analytics turf over the past few years. The cloud-native data platform for machine learning (ML) and artificial intelligence (AI) has built a solutions portfolio of optimized versions of open-source data processing engines such as Apache Spark, Presto, Apache Hive, and Airflow that allows enterprise-scale customers to process exabyte of data every month. In a nutshell, Qubole’s self-service platform enables multi-cloud data processing for AI/ML and analytics workflows.
With an impressive roster of clientele — Expedia, Lyft, Box, Grab, Comcast, Oracle, and Disney, Qubole says its prime purpose is to help customers bridge the gap with “improved access to data, no matter where it livesâ€. This end-to-end data activation is made possible by an enterprise-grade cloud-native data platform that allows batch and streaming ETL, ad hoc SQL queries, model training, and deployment — for analytics and machine learning.
Namit JainOpens a new window , Senior Vice President of Engineering at Qubole, who has deep expertise in data engineering and Big Data Analytics is an Oracle, Facebook, and Nutanix alum. In this edition of Meet the Disruptors, Jain shares why cloud deployment is key to big data analytics, how data lake architecture is allowing companies scale data processing abilities, and why diversity in the talent pool is an accelerator for the data engineering industry.
Qubole Grows Revenue by 573%, Earns Top Spot on Deloitte’s List
Six years after it was set up by former Facebook data engineers Ashish ThusooOpens a new window and Joydeep Sen SarmaOpens a new window , Qubole clinched 194th position on Deloitte’s Technology Fast 500 in November 2019, having grown its revenue by 573% in a short period and setting offices in New York City, San Francisco, London, Singapore, and Bangalore. Climbing up the data analytics bandwagon, the company still remains one of the very few that offer optimized versions of Spark, Presto, Hive, and Airflow with intelligent automation technology in its unified platform to help companies meet service-level needs and minimize cloud costs.
Jain shares the key differentiator is Qubole’s multiple public cloudOpens a new window partnerships, massive customer cloud cost savings along with its consistent growth played a major role in the company featuring in Deloitte’s Technology Fast500. Breaking out on the Fast500 will help Qubole gain credibility, expand the user ecosystem and roll out products and features that will go a long way in serving businesses in making informed decisions.
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Simplifying Big Data With Cloud-Native Data Lake
Cloud-native deployments on Amazon AWS, Microsoft Azure, and Google Cloud deliver high scalability, security, and faster time to market as compared to traditional on-premises data centersOpens a new window . Cloud service modelsOpens a new window have become the new norm for enterprise deployments in almost every category, including Big Data.
Even though organizations can scale their big data projects and implement a data-driven business culture with greater ease on the cloud, adopting a cloud deployment model requires a “cloud-first re-architectureOpens a new window †and a “platform approach†rather than a simple lift and shift of data applications and pipelines. With its modern cloud-native data lakeOpens a new window architecture, as opposed to a cloud data warehouse, Qubole provides enterprises a highly secure and efficient enterprise-scale platform for all data engineering, analyticsOpens a new window , and AI/ML needs.
In November, Qubole partnered with leading analytics major Tableau to enable companies to run business intelligence (BI) on data lakes with increased choice and simplicity. Thanks to the partnership, Tableau customers were able to query unstructured or semi-structured data on any data lake regardless of the storage file format – CSV, JSON, AVRO or Parquet, and also query multiple big data sources in quick time without changing their normal workflow.
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Qubole Promises Big Gains to Investors
Qubole is not alone in the race. One of the biggest vendors, Ali Ghodsi led Databricks, recently unveiled a new unified data management framework, pegged ‘lakehouse’ that fuses structured and unstructured data. Other competitors include Google BigQuery and Snowflake. Jain believes Qubole is a good bet for investors since it answers two critical questions that sit on an investor’s mind — the kind of returns cloud data technology would bring, and the ability to serve the company’s data needs at one go, one stop.
“We are an end-to-end, single platform engineered for efficient, enterprise-scale big data processing that supports 10X more users and data than any other. Moreover, not only does the platform help enterprises maximize efficiency, but also maximizes cost savings significantly (by 50% or more) and positively impacts service level agreements (SLAs) while handling diverse workloads across the big dataOpens a new window lifecycle. This is what the investors see – they see Qubole enabling businesses of all sizes and across industries to disrupt, thrive, and innovate using all of their data,†he says.
Qubole has demonstrated the capabilities of its unified platform on several occasions, helping companies improve their data processing and analytics capabilities. For instance, Ibotta’s data volume increased from 20 TB (terabyte) to 1 PB (petabyte) using Qubole’s new data acquisition and machine learningOpens a new window features. Similarly, TiVO has been able to process massive amounts of data efficiently and accurately – they have been able to scale up new products rapidly with a Data Lake using Qubole.
In February, Qubole clinchedOpens a new window the Best Cloud Business Intelligence or Analytics Solution award at the International Cloud Computing Awards program held in Santa Clara, California. The company was also named a leader in the 2019 Grid Report for Big Data Processing and Distribution after its features scored 90% on performance, reliability, and data transformation.
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Diversified Data Engineering Talent Pool Has Spurred Growth
According to Jain, Qubole has vastly benefited from acknowledging talent from all over the world and nurturing them. Aside from the company’s team based in the U.S., employees based in India, have shown massive growth in terms of technological developments as well as adaptability to new technologies, open-source or otherwise.
“Talent hired in India have demonstrated not only great skill sets but also high levels of accountability/ownership and self-drive. Hence, the need and justification to diversify our talent poolOpens a new window and build up a truly world class team,†says Jain.
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Integration With GCP Console a Game-Changer
Jain joined Qubole in February 2018 to head the company’s worldwide engineering management. He brought with him vast experience in databases, big data technologies, and the experience of scaling large engineering teams at Oracle, Facebook, and Nutanix. In the two years since he took over, Jain considers the Qubole unified platform’s general availability on Google Cloud as his biggest achievement so far as the same has enabled Qubole’s clients to enable low cost, high reliability, day-one self-service access and support for open source engines.
Some of his key achievements include the launch of Qubole Cost Explorer that helps ensure financial discipline and greatly decreases cloud costs, support for new Open Source versions for Spark, Presto and Hive, and Tableau Driver, Jupyter Notebooks, using staggered deployments for stability. Jain emphasizes the “Integration with GCP Console†that will help Google Cloud users to use Qubole Data Service transparently with user management and permissions being configured directly in GCP is a potential game-changer.
About Namit JainOpens a new window :
Namit brings more than two decades of industry experience in data warehousing and big data technologies. Before joining Qubole, Namit worked at Nutanix, where he started the Nutanix India office from scratch and grew it to about 500 people. Prior to that, he was part of the data infrastructure group at Facebook and became the first PMC chair for Apache Hive, which is used across the industry. He has been awarded 30+ patents and has publications in many conferences. Namit holds a Master’s degree from the University of Minnesota and a Bachelors from IIT Kanpur.
About Qubole:
Qubole provides a cloud-native data platform for analytics and machine learning that quickly activates large quantities of data for all users while lowering costs. Built by the team who built Facebook’s data platform, Qubole serves some of the largest data-driven companies such as Lyft, Expedia, Box, and Oracle.
About Meet the Disruptors:
Meet the Disruptors features disruptive players across specific verticals in Big Data, Cloud, AI-as-a-Service, and other domains. The column profiles the company’s business model, technology stack, and business strategy and how it foresaw an opportunity that incumbent players missed and built a profitable business model around it.
Do you think cloud-native data platforms have the potential to transform big data analytics and help achieve business outcomes? Comment below or let us know on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We’d love to hear from you!