Kai Wähner

CORE

Global Field CTO at Kai Waehner GmbH + Kestra

Company website: https://www.kai-waehner.de

Effeltrich, DE

Joined Jun 2010

https://www.kai-waehner.de

About

Kai Waehner is Advisory Field CTO at his own company, Kai Waehner GmbH, and Global Field CTO at Kestra. He advises enterprises, system integrators, and technology vendors on data integration, process intelligence and workflow orchestration, trusted agentic AI, and enterprise architecture. His career spans Talend, TIBCO, and Confluent. Kai publishes independent technology landscapes with no vendor sponsorship. He is a regular speaker at international conferences and a book author. He shares industry use cases and architecture best practices on his blog: www.kai-waehner.de. Contact: @KaiWaehner / linkedin.com/in/kaiwaehner.

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Reputation:	8664
Pageviews:	3.6M
Articles:	168
Comments:	5

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Data

IoT

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Articles
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Articles

MQTT, Kafka, NATS, or Zenoh? Choosing Edge-to-Cloud Messaging by Traffic Pattern

Telemetry, control, site sync, and delivery to people have different physics. Here's how MQTT, Kafka, NATS, Zenoh, event mesh, and last-mile platforms map onto them.

October 27, 2026

· 817 Views

How Kestra Unifies Enterprise Workflow Orchestration and Agentic AI

Learn how Kestra unifies enterprise workflow orchestration across IT scheduling, data pipelines, infrastructure automation, business processes, and AI agents.

October 21, 2026

· 1,000 Views

Data Integration Landscape 2026: Event Streaming, API, and Batch in the Era of Agentic AI

Why event-driven architecture belongs at the center of enterprise integration, and how every major vendor maps across three paradigms.

October 20, 2026

· 1,872 Views · 1 Like

Complex Event Processing (CEP) With Apache Flink: What It Is and When (Not) to Use It

A practical guide to complex event processing (CEP) with Apache Flink: what it is, when to use it, and how to implement it in production.

October 16, 2026

· 1,231 Views

YAML vs XML vs JSON: History, Trade-offs, and Where Each Wins in the Age of Agentic AI

XML, JSON, and YAML compared: history, trade-offs, and where each wins, plus why JSON Schema is now the contract layer for AI agents.

October 5, 2026

· 968 Views · 2 Likes

Why Databricks and Snowflake Speak the Kafka Protocol: Ingestion vs Architecture

Databricks and Snowflake speak the Kafka protocol, but Kafka for lakehouse ingestion is not Kafka as an event-driven architecture.

September 30, 2026

· 3,441 Views · 1 Like

MCP vs REST/HTTP API vs Kafka: The Architect's Guide to Agentic AI Integration

MCP, Kafka, and REST APIs are not the same: this comparison maps each to the right layer of your agentic AI architecture.

September 18, 2026

· 4,120 Views · 1 Like

The Trinity of Modern Data Architecture: Process Intelligence, Event-Driven Integration, and Trusted Agentic AI

Process intelligence, event-driven integration, and trusted agentic AI must be designed as one converged architecture for real business value.

September 16, 2026

· 3,011 Views · 1 Like

dbt Meets Apache Flink: One Workflow for Data Engineers

dbt meets Apache Flink: one SQL workflow for data engineers across Snowflake, BigQuery, Databricks, and real-time streaming pipelines on Confluent Cloud.

September 15, 2026

· 2,053 Views · 1 Like

Stream Processing on the Mainframe With Apache Flink: Genius or a Glitch in the Matrix?

Apache Flink on the IBM mainframe connects real-time processing with core systems, enabling hybrid cloud and AI without full migration.

September 10, 2026

· 2,921 Views · 1 Like

Dashboards and Queries for Apache Kafka

Apache Kafka dashboards: when to use them, how to support different query types, and why a context engine often makes the difference.

September 10, 2026

· 2,763 Views · 2 Likes

Cybersecurity with a Digital Twin: Why Real-Time Data Streaming Matters

Digital Twin for Cybersecurity with Data Streaming using Kafka, Flink and Sigma enables real-time visibility to detect and respond to threats.

April 20, 2026

· 2,918 Views

Scaling Kafka Consumers: Proxy vs. Client Library for High-Throughput Architectures

Scaling Apache Kafka consumption requires new patterns; proxy layers and client libraries offer practical solutions for high-throughput.

March 30, 2026

· 1,654 Views · 3 Likes

Online Feature Store for AI and Machine Learning with Apache Kafka and Flink

Real-time feature store powered by Apache Kafka and Flink enable fast, scalable AI personalization with fresh data and low-latency processing.

March 16, 2026

· 3,057 Views · 1 Like

Square, SumUp, Shopify: Data Streaming for Real-Time Point-of-Sale (POS)

POS systems are transforming into real-time, AI-driven platforms, fueled by mobile payments, Kafka, and Flink to empower every retail merchant.

March 9, 2026

· 3,556 Views

How Global Payment Processors like Stripe and PayPal Use Apache Kafka and Flink to Scale

How top payment processor companies like Stripe, PayPal, Payoneer, and Worldline use data streaming for real-time payments and fraud detection.

February 3, 2026

· 1,838 Views · 3 Likes

The Future of Data Streaming with Apache Flink for Agentic AI

Flink and Kafka enable real-time agentic AI by streaming fresh data and model context via the MCP standard for intelligent actions at scale.

January 21, 2026

· 2,412 Views

The Rise of Diskless Kafka: Rethinking Brokers, Storage, and the Kafka Protocol

Diskless Kafka stores all event data in object storage without using brokers for scalable and cost-efficient data streaming architectures.

January 9, 2026

· 2,113 Views · 2 Likes

Multi-Region Apache Kafka using Synchronous Replication for Disaster Recovery With Zero Data Loss (RPO=0)

Kafka isn’t one-size-fits-all. Choose between self-managed, serverless, or BYOC deployments. New RPO=0 options now enable zero data loss for real-time applications.

January 9, 2026

· 1,858 Views · 2 Likes

Agentic AI Using Apache Kafka as Event Broker With the Agent2Agent Protocol (A2A) and MCP

Agentic AI becomes scalable and production-ready when powered by Apache Kafka with MCP and A2A for real-time, decoupled agent communication.

November 4, 2025

· 2,625 Views · 7 Likes

The Top 20 Problems With Batch Processing (and How to Fix Them With Data Streaming)

20+ hidden issues with batch processing — like data loss, duplication, and latency — and why data streaming is the smarter solution.

October 8, 2025

· 2,455 Views · 5 Likes

Real-Time Model Inference With Apache Kafka and Flink for Predictive AI and GenAI

Learn how data streaming with Kafka and Flink enhances AI/ML model inference, enabling low-latency, scalable predictions in real-time business use cases.

August 22, 2025

· 1,966 Views · 2 Likes

Fraud Detection in Mobility Services With Apache Kafka and Flink

Mobility services like Uber and Grab use data streaming with Kafka and Flink for fraud detection by applying AI and machine learning in real-time.

July 17, 2025

· 5,187 Views · 1 Like

The Shift to Open Industrial IoT Architectures With Data Streaming

Modernize OT with Data Streaming, Kafka, MQTT, and OPC-UA to replace legacy middleware, enabling real-time data + scalable cloud integration.

July 4, 2025

· 3,185 Views · 1 Like

Replacing Legacy Systems With Data Streaming: The Strangler Fig Approach

Modernize legacy systems without the risk of a full rewrite. Strangler Fig + data streaming enables scalable, real-time transformation.

July 1, 2025

· 1,730 Views · 4 Likes

Top Trends for Data Streaming With Apache Kafka and Flink

Explore how Apache Kafka and Apache Flink are transforming data streaming, powering real-time analytics, and shaping cloud and future-ready business systems.

June 18, 2025

· 2,914 Views · 1 Like

What is Microsoft Fabric for Azure Cloud (Beyond the Buzz) and How It Competes with Snowflake and Databricks

Microsoft Fabric is a lakehouse built on OneLake Storage in Azure Cloud and competes with Databricks and Snowflake for data analytics and AI.

June 3, 2025

· 2,346 Views · 2 Likes

Comparing SaaS vs. PaaS for Kafka and Flink Data Streaming

SaaS vs. PaaS Data Streaming: Understand key differences in Apache Kafka and Flink cloud deployments to balance control, cost and ease of use.

May 2, 2025

· 4,109 Views · 1 Like

Stateless vs Stateful Stream Processing With Kafka Streams and Apache Flink

Concepts and benefits of stateless and stateful stream processing with Kafka Streams and Apache Flink vs. databases and data lakes.

April 21, 2025

· 7,354 Views · 5 Likes

Why Generative AI and Data Streaming Are Replacing Visual Coding With Low-Code/No-Code Platforms

Low-code or no-code tools simplify development but have limitations. Generative AI and data streaming (Kafka, Flink) reshape real-time, scalable workflows.

April 14, 2025

· 2,889 Views

Comments

Spring Integration and Apache Camel

Jan 11, 2012 · Biju Kunjummen

I just wrote an article, which explains my experiences with Apache Camel and its alternatives Spring Integration and Mule ESB:

Spoilt for Choice: Which Integration Framework to use - Spring Integration, Mule ESB or Apache Camel?

Best regards,
Kai Wähner (Twitter: @KaiWaehner)

Pros and Cons – When to use a Portal and Portlets instead of just Java Web-Frameworks

Oct 14, 2011 · Kai Wähner

Thanks for your comments.

@André: Well, you are right: You should not consider only product costs (they are not much cheaper for Liferay than for Oracle), but the whole development cycle. Maybe my article was a little bit unclear about this!

I see, you have a lot more experience with Portlets than me. We did not go any further, because we decided that a Portal / Portlets are not reasonable for our project.

Regarding the Oracle stack: We only evaluated the Portal which Oracle offered us combined with its Oracle SOA Suite (WebCenter). I did not make the choice, I just had to evaluate it...

@Erron: As already mentioned, I do not have much experience with Portlets. We decided that it is too much extra effort without creating a prototype or so :-) Thus, I cannot tell you anything about the GWT Portlet plugin. Maybe someone else can?

Open Source Integration With Apache Camel and How Fuse IDE Can Help

May 19, 2011 · mitchp

Hey Jonathan, this article is a good overview about Apache Camel. I can confirm that all promises about easier integration are true (because you always use the same DSL). I already tried out the BETA of Fuse IDE and wonder if there are plans for supporting Java DSL in the future? Yes, I am one of the guys, who does not like too much XML configuration :-) Best regards, Kai Wähner (Twitter: @KaiWaehner)

Creating Application using Spring Roo and Deploying on Google App Engine

Apr 10, 2011 · Shekhar Gulati

Hey Shekhar,

good article. But did you also realize some relationships between entities? I think "OneToMany" and so on do not work with GAE?

Best regards,

Kai Wähner (Twitter: @KaiWaehner)

Apache Camel: Integration Nirvana

Jan 04, 2011 · Jonathan Anstey

Very nice introduction to Apache Camel! Thank you.