The back story is that, while Cloudera has made firm progress, not only in reaffirming commitment of over 90% of the installed base, and inching toward profitability after early post-Hortonworks merger stumbles, Wall Street is not quite so patient. Following its blockbuster IPO, Wall Street is looking for the next Snowflake and is hungrily eyeing Databricks, which has amassed over $1 billion in venture capital. Under private equity, Cloudera is hoping for a path that will look a lot like Informatica. It went private back in 2015 to help it transition to a subscription business and roll out a next-generation cloud service. Fast forward to the present and Informatica’s results are solid. They are on the home stretch of completing the platform makeover. Although overall revenues, as reported in a journal article last year, are only up modestly compared to when the business went private, subscription revenues are growing at a 40% compound annual rate, and annual recurring revenue has doubled. As noted above, Cloudera has accomplished some key goals post-merger. As Big on Data bro Andrew Brust reported at the time, it performed the heavy lift on product transformation, following up with a cloud-native version that runs in all public clouds, and then a private cloud edition running on OpenShift. Its renewal rates have been in the high 90 ranges, and Q1 FY 2022, reported yesterday, continued the steady increases in subscription and annual recurring revenues that have occurred over the past half dozen quarters or so. For all the transitions that Cloudera has made, it still has yet another major pivot ahead of it: expanding the base to new customers. That’s easier said than done as it requires, not “just” a platform that performs analytics, but an end-to-end experience that addresses all audiences, from, business users expecting self-service to data scientists who want to play with the raw power of Python. Rivals, such as Snowflake, Databricks, SAP, and even Oracle, are rolling out end-to-end services blending in ancillary services, such as data integration, visualization, and/or AutoML – all with a self-service bent and either deployed as multi-tenanted services or offering that as basic tier options. CDP Cloud is not there yet, and that’s the story of the two acquisitions that came in behind the headlines. CDP may have become a more coherent platform and the zoo animals may have been finally caged. But, like Hadoop before it, the platform remains fairly complex to set up; lots of knobs and dials are still there. That’s fine for Cloudera’s existing installed base, comprised of organizations with the technical expertise for caring and feeding the zoo animals of Hadoop. But to draw a broader base, going from Fortune 100 to Fortune 5000 or 10000, the platform has to offer simpler options without all the knobs, not to mention more economical multi-tenanted services. Enter Cazena and Datacoral. Both companies are quite modest in size, each of which counts maybe a few dozen in staff and only modest venture financing in the tens of millions. But their technologies could help Cloudera finally broaden the appeal of its cloud data platform. Founded in 2014, Cazena is a company that has been on our radar for roughly five years. We have caught up with CEO Prat Moghe on several occasions. With company founders having come from Netezza, Cazena’s focus was delivering the data lake as a cloud-based white-glove managed SaaS offering, standardizing on a single system image, orchestrated data ingestion, and related tooling. By contrast, with CDP Public Cloud, and its predecessor Altus, the customer needed their own DevOps engineers to configure installations, with Cloudera handling the software patching and updating. We expect that once the Cazena technology gets absorbed into CDP Cloud, that Cloudera will introduce new editions with more self-service that will complement, not replace the existing CDP Public Cloud and Private cloud offerings. Datacoral is slightly younger, founded in 2016. It offers a SaaS cloud service that provides data integration and transformation pipelines and offers dozen of prebuilt connectors to common data sources to databases, application APIs, events, and file systems. It’s a common type of service; for instance, Azure Synapse Analytics embeds Azure Data Factory that provides similar capabilities for building data pipelines. And Fivetran has built a popular service for in-database data transformations. Oracle has also expanded its Autonomous Data Warehouse cloud service in a similar fashion. There is also one other important key technology piece that Datacoral brings to Cloudera: a multitenant cloud platform. We could imagine a new multitenant tier that combines the prebuilt, managed Cloudera services from Cazena, with the economics of a multitenant offering courtesy of Datacoral. The move is redolent of when MongoDB acquired MLab; while MongoDB already had its own Atlas managed cloud service, MLab added a missing self-service component. Private equity has become a popular financing option for technology firms with Cloudera just the latest tech player to go that route. But in the bigger picture, Cloudera is competing in a landscape where analytic platforms are morphing into self-service end-to-end offerings. The private equity financing might have grabbed the spotlight, but the acquisitions could be the sleeper. Disclosure: Cloudera is a dbInsight client.
