Extend Kafka with Diffusion

Many teams using Confluent Kafka for its powerful event-streaming capabilities find themselves facing unexpected costs, complexity, and performance limitations, especially when delivering data over the internet to web and mobile applications. 

The Hidden Trade-Offs of Big Stream Platforms

Let’s be clear: Kafka (and Confluent’s managed version) are great at what they’re built for – back-end event streaming, analytics pipelines, and resilient storage for replay. But the same durability and backend muscle that make them reliable at scale can make them heavy-handed when your priority shifts to low-latency edge delivery or millions of lightweight, constantly connected clients.

If you’ve ever tried to wire a Kafka topic straight to a mobile app feed, you probably know the pain points:

❌ Extra plumbing to fan data out to the edge

❌ High overhead for simple use cases like UI updates

❌ No built-in session awareness for downstream clients

❌ Costly at high connection scales

These gaps often lead teams to bolt on yet another tool or worse, reinvent the wheel in code.

Enhance your existing Confluent investment without a costly migration 

This is where “right tool for the job” matters. If your real-time needs live closer to your end user – the browser, the app, the device – a lighter, purpose-built delivery layer can offload a ton of complexity.

For example, DiffusionData is one approach: it complements your existing Kafka backbone by handling session management, real-time filtering, and delta streaming at the edge. Here’s how we can help:

☑️ Slash Bandwidth & Infrastructure Costs: Reduce your data streaming and infrastructure costs by 75% and more with our intelligent delta-data technology, directly addressing one of the biggest drivers of high Confluent bills. 

☑️ Conquer the Last Mile: Reliably deliver real-time Kafka data to millions of web, mobile, and IoT clients over the internet where Kafka’s protocol can struggle with latency and high bandwidth use. 

☑️ Scale Easily: Seamlessly manage millions of unique data topics without the performance degradation or complexity seen in large-scale Kafka deployments, allowing for efficient personalisation. 

☑️ Accelerate Development: Empower your developers to build real-time applications faster with our low-code features and intuitive SDKs.

☑️ Enhance, Don’t Replace: Integrate DiffusionData with your existing Confluent platform in minutes using our pre-built Kafka Adapter to unlock immediate value and extend your data reach. 

☑️ Unlock AI’s Potential with Smarter Streaming: AI thrives on fast, precise data – but Kafka alone can’t always keep up with that demand. Diffusion enhances your Kafka environment to deliver the right data, to the right place, at the right moment – powering real-time intelligence at scale.

Find out more about extending Kafka with Diffusion, or get in touch to discuss how you can dramatically reduce your TCO while extending the power of your Confluent streams. 


Further reading

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Architecting Real-Time Systems: It’s More Than Just Fast Updates

July 01, 2025

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The Game-Changer: Change Data Capture (CDC)

March 17, 2025

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3 Common Misconceptions About Scaling Real-Time Infrastructure

June 05, 2025

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