Latest figures from Confluent:
- Fourth quarter subscription revenue of $302 million, up 20% year over year; Confluent Cloud revenue of $169 million, up 23% year over year
- Fiscal year 2025 subscription revenue of $1,120 million, up 21% year over year; Confluent Cloud revenue of $624 million, up 27% year over year
- 1,521 customers with $100,000 or greater in ARR, up 10% year over year
I think the IBM deal (acquisition for 11 billion) from last December somehow got lost. So a few thoughts on it after the strong figures.
I believe that with this acquisition IBM is building the "nervous system" for real-time AI and, in my view, a potential game changer for enterprise data. Yes, this also increases the debt again, but only this deal could be paid for in less than 12 months with the current cash flow.
What is Confluent doing?
Imagine this: Your company produces millions of data events every day - purchases, sensor data, transactions, IoT signals.
The problem: Traditional databases store as "batches", meaning that old data is always analyzed.
Confluent's solution is quasi real-time data streams! Based on Apache Kafka, Confluent transports data live - like a super highway for company data.
What kind of use cases can these be?
- Fraud detection at banks in milliseconds
- Supply chains react live to problems
- AI models receive up-to-date data instead of outdated data
- Netflix, Uber, Goldman Sachs, BMW are already using it
Why is this a perfect fit for IBM?
It's a massive strategic move by IBM. To understand why this is so logical, you have to look at what IBM wants to be today: the king of hybrid cloud and artificial intelligence (AI) for businesses.
Here are the three main reasons why this purchase is a "match made in heaven":
The "central nervous system" for AI (watsonx)
AI models (like IBM's watsonx) are only as good as the data they are fed with. If the data is "old" (from the warehouse/snowflake), the AI is slow.
- The highlight: Confluent delivers data in real time. With Confluent, IBM can now offer its customers an AI that reacts immediately to events (e.g. fraud detection at the moment of payment or immediate adjustment of supply chains).
The "Switzerland" of data (hybrid cloud)
With the acquisition of Red Hat (2019), IBM has made it clear that companies should not only store their data in one provider (such as only $AMZN (-1,61%) or only $GOOGL (-1,18%) ), but distributed everywhere.
- The synergy: Confluent is technologically neutral. It connects data, regardless of whether it is stored in a private cloud, on Azure or on old IBM mainframes. This makes Confluent the perfect "connective tissue" for IBM's hybrid cloud strategy.
From "warehouse manager" to "logistics giant"
IBM previously had powerful tools to process and store data, but lacked the modern "pipeline". IBM is thus building the data infrastructure for the AI era. While everyone is talking about LLMs, IBM has understood: The winner in the AI race is the one with the best data pipelines or data has which, in this case, is already with the enterprise customers. The big bet: a full-stack enterprise AI platform beats individual components. IBM vs. Snowflake, Databricks, AWS Kinesis.
IBM's advantage: Open Source + Hybrid Cloud + Neutral + Enterprise Trust
I find the focus on enterprise customers very exciting. I remain invested and may buy more in the current phase. The share is a hefty 18% away from its high.
The big question is will the bet work? Opinions on IBM ?
