Off the back of a breakout year where we grew revenue 500%, today we announced the latest milestone in the Unravel journey – we closed a $35M Series C funding round.
Along with our data ecosystem partners, we are seeing unprecedented demand for solutions to complex, business-critical challenges in dealing with data.
Consider this. Data Engineers walk into work every day knowing they’re fighting an uphill battle. The root of the problem – or at least one problem – is that modern data systems are becoming impossibly complex. The burgeoning amount of data being processed in organizations today is staggering, where annual data growth is often measured in high double-digit percentages. Just a year ago, Forbes reported that 90% of the world’s data was created in the previous two years.
And with that data growth has come rapid growth in the number of applications for ingesting, correlating and analyzing that data. Each component of a data pipeline is by nature a specialist, and it takes lots of specialists to make data deliver results – and, more importantly, insights. This is a problem that touches virtually every corner of the world of business. And the pressure to perform and make data “work” is unrelenting.
In our own research from November 2018, Unravel found that three-quarters of businesses expect their big data stack to drive profitable business applications by the end of 2019 – but only 12% were seeing this value at the time.
The media is rife with stories prophesying magnificent discoveries to be made when data converges with artificial intelligence-driven models. Some of these discoveries have been made, but many more are still to come. Too often, these discoveries are over the horizon or well beyond the horizon, as data practitioners struggle with data systems that create more hurdles than they knock down.
Old Technologies Cannot Solve New Problems
Model-driven insights from data is what every business aspires to. The need for reliable and scalable application performance spawned the development of Application Performance Management (APM) and log management tools, two pioneering technologies in the race to make sense of new, multi-tier web architectures. The problem is that those technologies fell short because they were not designed and built for modern data systems. From the standpoint of the Data Engineer, the metrics and graphs those technologies deliver fall flat, when the team needs actual recommendations and answers to the issues faced multiple times every day.
“It’s clear that enterprises continue to struggle with dealing with the enormous amount of data that fuels their businesses. Legacy approaches have failed, and they need to modernize their systems or risk being made irrelevant,” said Venky Ganesan, managing director, Menlo Ventures.
Dealing with Overwhelming Complexity
Although it might be trite, it’s worth mentioning that every business is becoming a data business. That’s why most businesses consider data management systems such as Spark, Kafka, hadoop and NoSQL as their critical systems of record.
Data pipelines are so complex that they are outgrowing our ability to manage them. That’s because these systems have so many interdependencies that solutions lie beyond human intuition or deduction. And that’s why Unravel talks a lot about the importance of full-stack visibility for optimizing the performance of data-driven applications. We obsess over the need to explore, correlate, and analyze everything in your big data environment, search for dependencies and issues, understand how data and resources are being used, and discover how to troubleshoot and remediate issues.
And we believe in the promise of AI. That’s why Unravel integrated a powerful AI engine to deliver recommendations that drive more reliable performance in modern data applications.
Cloud Complicates Everything
As businesses migrate their data-focused applications and their data to the cloud, they face the fact that many cloud platforms provide only minimal siloed tools for managing these workloads.
In response, Unravel, unveiled its newest version of the Unravel platform, which focuses squarely on the unique requirements of hosting data-focused applications in the cloud. That release took the AI, machine learning, and predictive analytics that are the hallmarks of the platform and enabled users to assess which apps are the best candidates to move to the cloud – based on the customer’s own defined criteria.
The release also gave users the tools to validate the success of their cloud migration and predict capacity based on their specific application workloads. At the time, I noted that many unknowns around cost, visibility and migration had prevented this transition to the cloud from occurring more quickly. But that is no more.
Continuous improvement: although the term is dated, the concept is still as timely as ever. And it’s a mantra of many businesses today that are never content, even with their highest achievements.
Continuous improvement is just the latest growth driver in modern data systems as well, and it’s being built on models. In turn, these models are built on closed-loop data. “When built right, these models create a reinforcing cycle: Their products get better, allowing them (businesses) to collect more data, which allows them to build better models, making their products better, and onward,” said Steven Cohen and Matthew Granade of Point72 Ventures, an investor in Unravel Data.
If anything is keeping CIOs from meeting their OKRs, #1 on that list is likely data system complexity. Well, complexity is here to stay! In our data-driven world, gains come when we deal with the inevitable complexities and move beyond them. At Unravel, we think big data can do better, and we’re here to help it along. By radically simplifying the way you do data operations, how your models perform and ensuring big data lives up to your expectations – both today and tomorrow.
Read on to learn more about today’s news from Unravel.
Point72 Ventures leads funding round to address performance and complexity challenges of modern data applications and cloud migration initiatives
PALO ALTO, Calif.,—May 14, 2019—Unravel Data, the only data operations platform providing full-stack visibility and AI-powered recommendations to drive more reliable performance in modern data applications, today announced it has raised $35 million in an oversubscribed Series C funding round. Point72 Ventures, founded by renowned hedge fund investor Steve Cohen, led the round with participation from Harmony Partners, and existing Unravel investors Menlo Ventures, GGV Capital and M12 (Microsoft Ventures).
“At first glance, application performance management (APM) may seem like a problem that has been addressed by the APM and log management vendors such as AppDynamics, New Relic, Splunk, and DataDog. The reality is that these solutions were not initially built for modern data systems. By being natively built with modern IT in mind, Unravel can cost-effectively deliver the data application awareness and AI-powered recommendations, resolutions, and answers that organizations demand,” said Mike Leone, senior analyst at ESG. “Additionally, as workloads migrate to cloud platforms, the complexity of multiple systems, locality of services and technologies, different operating and pricing models, and constantly changing dependencies throughout the data pipeline add higher levels of risk to migrations, performance optimization challenges, and cost concerns.”
“Most industry-leading companies are now software businesses, and a majority of those businesses are running on top of mission-critical big data applications,” said David Dubick, Partner, Point72 Ventures. “These big data tailwinds have created a demand for tools to monitor, optimize and secure these systems, and Unravel is uniquely positioned to address this need in the marketplace.”
“CIOs in our network told us story after story of traditional application monitoring tools failing in a big data context because those tools were designed for the world of the past. And we didn’t just hear this problem from third parties, we were seeing it at Point72 as well,” said Matthew Granade, Chief Market Intelligence Officer at Point72 and Managing Partner of Point72 Ventures. “This new architecture requires a different product, one built from the ground up to focus on the unique challenges posed by big data applications. Unravel is poised to capture this emerging big-data APM market.”
Company Momentum Highlights
Today’s funding news follows a year of significant momentum for Unravel as evidenced by a series of milestones:
“Every business is becoming a data business, and companies are relying on their data applications such as machine learning, IoT, and customer analytics, for better business outcomes using technologies such as Spark, Kafka, and NoSQL,” said Kunal Agarwal, CEO, Unravel Data. “We are making sure that these technologies are easy to operate and are high performing so that businesses can depend on them. We partner with our customers through their data journey and help them successfully run data apps on various systems whether on-premises or in the cloud.”
Unravel Reviews on Gartner Peer Insights:
“Key Software Product for Today’s Modern Data Applications And Systems” March, 2019
“Enterprises are turning to technologies like Spark, Kafka, MPP, and NoSQL to embrace a data-centric approach to their business. The challenge is that there are massive skills shortages associated with architecting, managing, and optimizing all these integrated tools supported by numerous vendors across a data pipeline. In fact, on average, organizations work with 37 different vendors across their data pipeline today. Many of the technologies they rely on have their own monitoring and management tools, and this exacerbates the problem, creating operational silos and ultimately preventing end-to-end insight,” said Mike Leone, senior analyst at ESG. “How can organizations effectively utilize a wide range of applications like customer analytics, fraud prevention, and predictive maintenance that rely heavily on next-generation technology like AI and machine learning? By turning to a comprehensive data operations platform. Unravel allows customers to manage and optimize all their data pipelines from one location. By using AI-driven recommendations and automation, a high percentage of manual troubleshooting can simply be eliminated, enabling data operations teams to be proactive in preventing future issues.”
“As enterprises of every size choose the Azure Cloud platform to build and deliver their modern data, Unravel has proven an important tool to help enterprises operationalize this data and drive tangible value to the business,” said Rashmi Gopinath, partner, M12 Ventures. “Azure and Unravel have worked closely on product development and go-to market execution and are well positioned to meet this market demand.”
“There’s a tremendous need to enable organizations to maximize the value of their data infrastructure investments,” said Mark Lotke, founder and managing partner, Harmony Partners. “Unravel fills that gap perfectly as the only company that is truly using machine learning and an AI-driven platform to optimize and operationalize data-driven applications and the data systems they depend on at scale. The Unravel team demonstrated incredible growth in 2018 and is poised for an even bigger year in 2019 as demand for data operations solutions accelerates.”
“It’s clear that enterprises continue to struggle with dealing with the enormous amount of data that fuels their businesses. Legacy approaches have failed and they need to modernize their systems or risk being made irrelevant. Unravel is leading the pack in providing technology innovations that provide this competitive edge and fuel the next generation of cloud and hybrid cloud data services,” commented Venky Ganesan, managing director, Menlo Ventures.
“Since we led the company’s B round, we have been blown away by the market momentum that Unravel has achieved in a short space of time. There is clearly an unmet need in large enterprises for solving the complexity and operational challenges they face as they transition to being data driven and cloud first,” said Glenn Solomon, Managing Partner, GGV Capital. “Current approaches are failing these data ops teams and Unravel has come to market with technology innovation and go-to-market execution that is solving real world problems, today.”
About Unravel Data
Unravel radically simplifies the way businesses understand and optimize the performance of their modern data applications – and the complex pipelines that power those applications. Providing a unified view across the entire stack, Unravel’s data operations platform leverages AI, machine learning, and advanced analytics to offer actionable recommendations and automation for tuning, troubleshooting, and improving performance – both today and tomorrow. By operationalizing how you do data, Unravel’s solutions support modern big data leaders, including Kaiser Permanente, Adobe, Deutsche Bank, Wayfair, and Neustar. The company is headquartered in Palo Alto, California, and is backed by Menlo Ventures, GGV Capital, M12, Point72 Ventures, Harmony Partners, Data Elite Ventures, and Jyoti Bansal. To learn more, visit unraveldata.com.
The name Unravel Data is a trademark of Unravel Data™. Other trade names used in this document are the properties of their respective owners.
Jordan Tewell, 10Fold