Last week, I covered Apache Kafka in depth, as a popular, open-source platform that is heavily utilized as the underlying infrastructure for distributing real-time streams of data. Besides being a centralized data pipeline for interconnecting the continuous flow of data across systems & apps, it can also be utilized for event streaming (tracking triggered events) – which can serve as the backplane for microservices and tracking database changes – and for stream processing (real-time analytics and data processing), via Kafka Streams (inline microservices and stream API) and ksqlDB (a SQL interface over streaming data).
Now that we know the open-source Kafka software, let's finally dive into Confluent, the enterprise company that was formed around it. As mentioned before, Confluent has a very similar structure to MongoDB and Elastic, being a company that supports the core open-source Kafka platform with enterprise enhancements & support, as well as having a SaaS service for managed hosting of their enterprise platform across the major cloud providers.
Confluent's core philosophy -- and where they are taking their platform -- is overly covered in the S-1/A, and was expanded upon in the earlier Kafka deep dive. They see many use cases for their platform around how data must be centralized in streams, which can then be leveraged further via stream processing.
Let's discuss how they got here, how the financials look, and what I see as the major competition and moves from here.