IBM's Acquisition of Confluent: What It Means for Kafka's Future and Your Data Strategy

IBM’s announcement that it will acquire Confluent has shaken up the data streaming and event-driven architecture world. For years, Apache Kafka has been the backbone of real-time data systems, and Confluent built a strong commercial ecosystem on top of it. Now, with IBM stepping in, the enterprise data landscape is shifting again.

If you’re a technology leader, architect, or platform owner, the big question is simple: Does this acquisition help you — or create new risks for your streaming strategy?

In this blog, we’ll consider past OSS acquisitions to predict how Confluent customers may be impacted. We will also evaluate whether switching to open source Kafka makes sense, and what companies should keep in mind as they evaluate their options.

A Familiar Pattern: Lessons From Previous OSS Acquisitions

Popular open source projects changing hands through acquisitions is not a new phenomenon, of course. Some of the most notable examples from the past 20 years:

• Oracle and Java, through the Sun Microsystems acquisition (2010)
• IBM and RHEL, through the Red Hat acquisition (2019)
• Broadcom and Spring Framework, through the VM Ware acquisition (2023)

Acquisitions like these create uncertainty for the organizations deploying open source technologies, as they wonder whether they can still rely on the community software they're building upon. 

Consider CentOS: For a long time, it was viewed as a stable and reliable alternative to Red Hat Enterprise Linux (RHEL). However, when Red Hat abruptly retired CentOS in favor of CentOS Stream, the paradigm changed. CentOS Stream is not a drop-in replacement for RHEL; it’s a preview of what could eventually end up in RHEL. As a result, organizations that depended on CentOS for either QA or production environments had to change course. (Things got messier still when Red Hat restricted RHEL source code access.)

Similar scenarios have played out in the infrastructure and automation space. Many panicked when HashiCorp switched Terraform’s licensing from open source (MPL 2.0) to source available (BSL 1.1), and there continues to be confusion around Red Hat’s Ansible Tower (now deprecated) and Ansible Automation Platform versus AWX, the open source upstream at the core of both. 

These pivots can be unsettling for implementers who don't know what features may change, where new development will occur, and what might slip behind a paywall next. Likewise, organizations utilizing Confluent Cloud or Confluent Platform may now have concerns about Kafka’s direction under IBM.

The Upside: More Visibility for Streaming and Kafka

IBM’s move validates something the industry has felt for a while: Real-time data streaming is becoming foundational to modern applications and enterprise AI.

This acquisition will shine a brighter spotlight on event streaming and push more organizations to rethink their data pipelines, modernization plans, and how real-time data fits into their AI initiatives.

That increased attention is good for the entire ecosystem — including open source Kafka.

Potential Risks for Confluent Customers

Whenever a large enterprise vendor acquires a critical infrastructure provider, customers immediately wonder:

• Will prices go up?
• Will licensing change?
• Will the platform become tightly bundled into a larger proprietary ecosystem?
• Is this still the best long-term architecture for my team?

These are reasonable questions and Confluent customers are asking them on forums like Reddit. One user in the Apache Kafka subreddit (r/apachekafka) posted “As for the acquisition, I can’t see it being good…I can’t imagine customers not getting squeezed further.”

Based on the history covered earlier, here's what we predict will follow the IBM Confluent acquisition: 

Pricing Changes

• IBM's business model typically involves bundling value-added features and services into enterprise pricing agreements.
• This means some organizations will pay higher prices for features or services they don't use.

Roadmap and Support Shifts

• Support timelines and the frequency of upgrades could change under IBM's leadership.
• Large vendors often streamline product offerings after an acquisition, which may not align with existing customer needs.

Increased Vendor Lock-in

• IBM will likely incentivize integrating Confluent's offerings more deeply into its own ecosystem (e.g., IBM Cloud, other IBM software).
• This could reduce the portability and flexibility that many organizations value in their data infrastructure.

Potential Alternatives to Confluent Kafka

The underlying technology for Confluent Kafka is Apache Kafka, and it has firmly cemented itself as the industry standard for data streaming. It’s proven, mature, and supported by a massive community.

Many teams originally adopted the Confluent ecosystem because they wanted convenience. However, if IBM takes Confluent in a more vertically integrated direction — which is likely — teams that value independence may not want to follow them down that path.

In light of this acquisition, organizations should be asking:

• “Can we get the same performance and reliability with open source Kafka?”
   (Short answer: Yes — and often more cost-effectively.)
• “Can we migrate off Confluent without breaking everything?”
   (Yes — with the right migration plan.)
• “Is it worth avoiding uncertainty and taking control of our own streaming future?”
   (For many teams, absolutely.)

With the IBM acquisition, reassessing vendor dependencies is not only smart — it’s strategic. It’s the perfect time for Confluent customers to take a second look at open, portable, cloud-agnostic Kafka deployments that give them:

• Full control
• No license restrictions
• No dependency on a single vendor’s roadmap
• Lower total cost of ownership
• The ability to run on any cloud (or on-prem)

For teams that aren't comfortable managing open source Kafka deployments in house, the best of both worlds approach is to work with a support vendor — like OpenLogic — that combines the affordability of open source with the SLA-backed support often required by internal and external compliance standards.

Learn more about OpenLogic Kafka support options here >>

Final Thoughts

For many companies, this acquisition is a chance to reevaluate their reliance on Confluent and consider what it would take to manage their real-time data infrastructure in-house. Open source Kafka — paired with independent support if additional expertise is needed — preserves flexibility and lowers long-term risk.

OpenLogic helps organizations:

• Migrate from Confluent to open source Kafka
• Reduce licensing costs
• Improve Kafka performance and scalability
• Deploy Kafka in cloud-agnostic or hybrid environments
• Implement best-practice architecture and operational models
• Get ongoing support without being locked into a single vendor
• Upskill their teams through Kafka training workshops

If you’re wondering whether staying on Confluent still makes sense, or whether shifting to open source Kafka is the smarter long-term move, explore OpenLogic’s Kafka solutions. 

Additional Resources

• Blog - Apache Kafka vs. Confluent Kafka
• Whitepaper - Decision Maker's Guide to Apache Kafka
• Blog - Kafka Migration: Best Practices and Common Challenges
• Guide - Enterprise Kafka Resources
• Webinar - Kafka Gone Wrong: How to Avoid Data Disasters
• Videos - How OpenLogic Supports Kafka: Solutions & Case Studies
• Solution - Kafka Service Bundle
• Blog - Kafka Cluster Configuration Strategies