We recently concluded our fiscal year on January 31st, and while there is always more to do and room for improvement, FY 2019 was a phenomenal year for us. We experienced tremendous revenue growth, made great strides in technology innovation, and continued building a world-class organization.
Validation of our efforts came from two independent sources. The first validation came from G2 Crowd, a peer-to-peer business solutions review platform that ranks products based on authenticated user reviews of products. The second validation came from Forrester, which uses a more traditional RFI-style format with a spreadsheet model to score vendors on various attributes.
What did they report? Well, G2 Crowd placed us in the High Performer Quadrant for their Big Data Processing and Distribution Software category, while Forrester placed us in the “Strong Contender” ring of their Cloud Hadoop/Spark Platforms Wave.
How Do I Feel About It?
Needless to say, I feel extremely happy about the validation from both of these sources.
What the G2 Crowd Ranking Means
The G2 Crowd validation delights me because it collates direct feedback from the users of our platform — a group that I care about deeply. Sixty out of 68 users who submitted reviews gave us a rating of four stars or higher on a scale of one star for poor to five stars for excellent. And I intend to reach out to the remaining eight reviewers to learn how we can serve them even better.
G2 Crowd reviews validate the very foundation on which Joy and I built this company. We use automation to deliver higher productivity and time to value from big data for machine learning and advanced analytics. Our platform works relentlessly on our customers’ behalf to reduce their cloud spend with innovations like workload-aware autoscaling, Spot buying, and real-time cluster management. The G2 Crowd Grid validates why our clients automated more than a million big data clusters with nearly 50 million machines in 2018. It also validates how our clients have saved hundreds of millions of dollars in cloud infrastructure spending.
But as I mentioned earlier, not all of our G2 Crowd reviews were as strong as they could have been. We still have work to do in our mission to help democratize big data for analytics and machine learning. We are working hard to improve our platform’s ease-of-use to make it even easier for our customers to manage their big data.
What the Forrester Wave Report Means
In the case of the Forrester Wave report, we are proud to be included on the list of companies that matter the most in big data processing using Hadoop and Spark in the cloud. And we are the only cloud-agnostic, cloud-native big data product to be included in this list.
The other products in this list are either legacy products trying to lift and shift their solutions from the data center world to the cloud world, or products offered by cloud vendors themselves. Understandably, they have a larger market presence. Although when you compare the growth rates between us and them, it’s just a matter of time until Qubole has a large — if not larger — market presence.
As always, there is actionable feedback from reports like these, which encourages us to continue working hard to improve our platform and win positive acknowledgment for our efforts. My recommendation to anyone considering a cloud-native big data processing platform is to evaluate its merits against your needs. While these types of reports are great reference tools, I would caution against relying on only them to select your big data processing platform. Sometimes the vendors identified as “leaders” might not be the best fit for your particular requirements — in the short term and long term. You may be better off with an emerging offering like ours, where the technology has been built from the ground up for the cloud.
Use a full body of research when buying products and setting strategy. Better yet, contact us to obtain a comprehensive Business Value Engineering analysis for your environment, and talk to others that use our platform so they can give you a practitioner’s perspective.