What we think about Confluent (CFLT)
Confluent in Three Words: Data in Motion
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Background
Confluent allows enterprise users to stream, connect, process, and govern your data with a unified Data Streaming Platform built on the heritage of Apache Kafka and Apache Flink.
In a typical company, there are often hundreds of different applications, databases, and data warehousing solutions. Generally speaking, querying data stored in databases or data warehouses, often referred to as “Data at Rest,” is a well-understood challenge.
However, forward-thinking businesses now seek to leverage data as it’s generated, necessitating an efficient messaging system for transferring data across numerous sources and consumers. Confluent addresses this as “Data in Motion.” On the surface, it may appear simple for software developers to establish communication channels between data producers and consumers. Yet, a brute-force approach to direct connectivity quickly encounters scalability issues. For instance, consider three data sources and three distinct applications consuming them, requiring developers to create nine connectors to facilitate “Data in Motion.” As complexity grows, connectivity becomes unwieldy.
Computer specialists solve these problems by building a “bus” (from Latin omnibus). The idea is to have a dedicated layer acting as an intermediary between data producers and consumers. A bus addresses the complexity issue and makes the data exchange problem scalable. Its sole purpose is to be excellent at facilitating the exchange of messages.
To solve this, computer specialists employ a “bus” concept, acting as an intermediary between data producers and consumers. This bus mitigates complexity and ensures scalability in data exchange. Buses are prevalent in computer architecture (e.g., Mac, iPhone, iPads), but when Confluent co-founder Jay Kreps and his team, former engineers at LinkedIn, sought a scalable software bus for interconnecting systems and applications, they found none. This prompted Kreps, Neha Narkhede, and Jun Rao to develop a system for LinkedIn, which they later released in 2012 as “Kafka” to the broader developer community under the Apache Foundation’s open-source umbrella. Apache Kafka emerged as a critical middleware system in the cloud era, gaining popularity among tech giants like Netflix, Airbnb, and Uber.
Apache Kafka remains open source, available for download and adaptation by anyone. Silicon Valley’s tech companies embraced it, but managing this complex middleware, which Jay Kreps likens to the “central nervous system” of modern enterprises, demands in-depth knowledge of distributed systems, cloud computing, and Kafka. In 2014, Confluent was founded with the vision of transforming Kafka into an “as-a-service” offering. Today, Confluent provides a re-architected version of Kafka, known for scalability, robust connectivity, SQL processing capabilities, and enterprise-grade security and governance features. Their fully managed Confluent Cloud solution is accessible on major public cloud platforms, including AWS, Azure, and Google Cloud Platform. Meanwhile, the self-managed Confluent Platform can be deployed on various platforms, such as private clouds, public clouds, and on-premises infrastructure.
Confluent’s ability to transcend cloud boundaries, operate across regions, and cater to businesses with extensive hybrid deployments across public clouds, private clouds, and on-premise infrastructure makes it an appealing choice for enterprises seeking to future-proof their data infrastructure layer.
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My overall takeaway is that it’s great to see the company hit that milestone of profitability. This proves that it can be a profitable business that can generate cash flows; rather than relying on constant secondary offerings at inflated valuations to fund its growth (and many SaaS companies have in years past).
I also believe that as operating profit and FCF become more meaningful...
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