If a technology vendor is fortunate, it can define an era. If it’s less than fortunate, that era will continue to define the vendor to its disadvantage once the growth potential of its original go-to-market model has begun to wane.
Cloudera Inc. has the ironic fortune to have named itself after an era it has only partially entered. We are very much in big data’s cloud eranow, but Cloudera has barely begun to address that inflection point. Meanwhile, as Wikibon discussed in our recent market study, the era with which Cloudera is most closely linked in the industry mind — Hadoop-based big data analytics — is starting to resemble a low-growth legacy business.
Here is Wikibon’s Peter Burris discussing that study, as well as Cloudera’s prospects, on theCUBE, SiliconANGLE Media’s video streaming studio, at the recent Big Data SV 2018 event:
Based in Palo Alto California, Cloudera was one of the principal vendors in Hadoop’s early commercialization. It has diversified well beyond that core market over the past several years as it expanded its solution footprint to address the needs of enterprise customers worldwide. Though it recently told Wikibon that it plans to provide all its solutions as managed platform-as-a-service or PaaS cloud offerings over the coming quarters, it currently offers only one. And that’s simply a beta of its managed data-preparation service, Cloudera Altus.
Even this offering, which provides managed extract-transform-load capabilities in the Microsoft Azure and Amazon Web Services clouds, is late to the game. Those providers and others, such as IBM, already offer ETL and a range of other data integration PaaS offerings in their own public clouds.
Of course, Cloudera has plenty of competitive strengths, among which are a substantial global customer base that it continues to build and which it continues to serve with new features, tooling and solution accelerators. Indeed, the vendor has just reported revenues, gross margins, customer acquisitions and international business that are substantially higher, on a year-over-year basis, in the latest fiscal quarter and year.
However, Cloudera’s heretofore successful “land-and-expand” growth strategy may fall victim to the fact that new customer acquisitions in the small- to mid-market are flocking to public cloud alternatives. And Cloudera’s margins may be slipping thanks to price competition from AWS, Microsoft Azure, Google Cloud and other public cloud providers.
But let’s not sell Hadoop short as a core Cloudera asset. In fact, Hadoop remains a linchpin for big-data file storage, batch processing, unstructured data refinement, queryable archiving and many other use cases. These are uses for which other, newer big-data analytics technologies — such as Spark, Kafka and TensorFlow — are not well-suited.
To address these and other core use cases, the company has built a comprehensive portfolio, Cloudera Enterprise Data Hub, around its market-leading distribution. As a single source for Hadoop-based analytics, streaming, modeling, governance, cataloguing and workload management, Cloudera remains a significant force in the industry.
But it still feels like something’s missing from Cloudera’s roadmap. The financial markets have registered that uncertainty by precipitating a significant drop in Cloudera’s stock price after the latest numbers hit the wires.
What’s missing from Cloudera’s story are robust profitability and momentum. For the latest fiscal quarter and year, it still showed significant operating losses, though these have narrowed considerably with respect to previous years. But what jumped out from the numbers was the softening outlook going forward, with net losses lingering, subscription revenue growth markedly decelerating and operating cash flow remaining in negative territory.
What will be needed to pull Cloudera out of this slump? One bright hope is its growth focus on the developer community, which is building the next generation of machine learning, deep learning and other artificial intelligence applications from their big data.
In fact, Cloudera has aggressively moved into the data-science pipeline tooling segment in recent years, providing a solution, Cloudera Data Science Workbench, that it cites as one of its fastest growing solution areas. That growth may not last, however, unless Cloudera begins to address the move by enterprises away from purely manual machine learning development toward more automated DevOps pipelines for operationalizing AI assets. It’s late to that game too.
Packaged vertical solutions are another possibility for continued revenue growth at Cloudera. It continues to build out its channel partner ecosystem to address these opportunities. Already, it’s a strong player in big-data analytics applications in cybersecurity, financial services, data protection, healthcare and genomics, and it seems to be expanding its presence in the booming “internet of things” edge analytics arena. But Cloudera’s ability to capitalize on these partner-led opportunities may be hamstrung by its traditional orientation toward direct sales.
However you look at it, Cloudera is having trouble finding its anchor in this new era. Are its best days behind it?
