Apache Kafka has become the backbone of modern, event-driven enterprises, but many organizations struggle to connect their most valuable data out of the stream. Connecting mainframe data to Kafka unlocks richer analytics, smarter AI, and a more complete view of the business. The challenge lies in bridging the gap safely, and without disruption.

Apache Kafka has become the nervous system of modern business. It powers event-driven applications, operational dashboards, and the instant digital experiences your customers now expect. Across industries, organizations are streaming billions of events daily—from mobile transactions to IoT signals to clickstream data—and using those insights to act in the moment. Yet even the most advanced Kafka architectures often miss a critical source of truth: the mainframe.

Over 80% of Fortune 100 companies rely on Kafka as their backbone for “data in motion.” But many of those same organizations still run their core business processes—payments, inventory, customer records—on mainframes that don’t natively connect to Kafka. The result is a modern data pipeline missing its most valuable context.

To unlock the full potential of Kafka, you need to bring mainframe data into the picture.

Why mainframe data belongs in the stream

Mainframes quietly power the transactions and records that define how large enterprises run. They contain the most accurate, trusted data in the organization—data that represents decades of business operations, customer history, and financial performance.

Integrating this data into Kafka doesn’t just expand your data footprint; it enriches it. When mainframe data flows alongside cloud, mobile, and web events, you can see not only what’s happening now but also what it means in context. You can understand patterns, relationships, and anomalies that aren’t visible from application data alone.

That combination of depth and immediacy is what gives modern data platforms their power.

Why connecting mainframes to Kafka isn’t easy

Mainframes weren’t designed to plug into modern event-streaming platforms. Traditional approaches of establishing this connection—batch jobs, ETL pipelines, or custom APIs—are expensive, fragile, and often introduce more risk than value. They also drain resources, as every data request requires specialized knowledge and time from the DBAs who maintain those systems. Additionally, home-grown connectors and manual extracts often fail to provide the stability and control enterprises need to confidently integrate mainframes into modern data architectures. For many organizations, this is where modernization stalls. The business wants the data, but IT can’t afford the disruption.

Protect what matters while enabling progress

Inside every enterprise are the experts who know the mainframe best—the DBAs who keep it secure and stable. They understand how critical those systems are, and they have good reason to be cautious about anything that could compromise them. That’s why the right approach is to empower these mainframe custodians with the tools and confidence to share data safely, without giving up control. When integration is non-invasive, fully governed, and access can be limited to read-only, DBAs can maintain the integrity of the system of record while opening new possibilities for the business.

A safer way to connect Kafka and the mainframe

That’s exactly what CONNX for Kafka was built to do. It bridges “data at rest” on the mainframe with “data in motion” in Kafka, and it does so securely, continuously, and without rewriting a single line of code.

CONNX for Kafka lets DBAs define and deploy connections in minutes, not weeks. Streams run in one direction, ensuring that mainframe performance and security stay intact. And because it speaks the native language of IBM Z data sources, integration happens without risk or disruption.

Non-disruptive integration. Connect safely and quickly without changing core applications.
Continuous synchronization. Continuously publish up-to-date mainframe transactions to Kafka topics.
Enterprise-grade governance. Maintain control, compliance, and visibility across the process. Integrates with enterprise security, auditing, and schema-management policies.

It’s the simplest way to extend Kafka’s reach to the systems you trust most.

What you can do once the data starts flowing

Bringing mainframe data into Kafka changes what’s possible across all of your business’s innovation projects. Once your mainframe is connected to your Kafka pipelines, you can blend decades of transaction history with streaming data to uncover trends and insights that were never visible before. Fraud detection models become more accurate. Customer analytics become more complete. Supply chain systems react faster to shifts in demand. Powerful internal AI systems, which rely on vast, high-quality, real-time data streams to train and adapt models, are placed within reach.

Kafka already delivers those streams, and CONNX for Kafka adds the dependable, structured data that makes them meaningful. The result is not just faster data movement, but smarter business movement.

Completing the picture

Kafka has become the connective tissue for digital business by redefining how modern organizations think about data movement. But the picture isn’t complete until the mainframe—the system that still runs your most critical workloads—becomes part of that story.

With CONNX for Kafka, you can extend the power of Kafka to your most valuable data source. No migrations. No rewrites. No downtime. Just secure, continuous streaming from the platform you trust most into the one that powers your future.

You’ve already invested in Kafka. Now make that investment pay off by unlocking the data that defines your business. Learn more about how CONNX for Kafka can help you stream mainframe data to your Kafka-powered systems and end data silos.

Sean Ryan

Unlock the full power of Kafka with mainframe data