Blog

This blog is your go-to guide for understanding event streaming. Discover how it works, why it matters, and how businesses leverage real-time data insights to stay ahead. From real-world applications in industries like finance and healthcare to tools like Apache Kafka.

Event streaming systems are essential for businesses that process real-time data to drive decision-making, enhance agility, and gain deeper insights. However, with numerous options available, selecting the right event streaming platform can be overwhelming.

Kafka vendor lock-in can limit your organization's flexibility, control, and cost efficiency. As companies increasingly turn to open-source Kafka, they unlock the potential for greater independence and adaptability. In this blog, we explore how migrating to open-source Kafka offers reduced costs, increased flexibility, and freedom from vendor restrictions.

Multiconsult, a renowned engineering and consultancy firm, is revolutionizing its operations by leveraging event streaming to enhance efficiency and responsiveness. With over 100 years of expertise, the company is focused on innovation and staying ahead of technological trends. Their recent adoption of event streaming solutions is driving operational excellence, contributing to record-breaking financial results in 2024. Discover how Multiconsult is transforming its data strategy to maintain its competitive edge.

This blog dives deep into Kafka Connect clusters, unraveling their structure, scaling strategies, and task management processes. Whether you're designing a high-availability system, troubleshooting task distribution, or scaling your pipeline for performance, this article provides a comprehensive look at how Kafka Connect clusters operate.

For years, Zookeeper has been integral to Kafka deployments as a reliable metadata management system. However, with its limitations and Kafka’s evolution through KIP-500, the shift to KRaft—a self-managed metadata quorum—marks a new era. This transition is critical as Zookeeper’s deprecation accelerates, with its removal planned in Kafka 4.0. Adapting now ensures your Kafka clusters remain future-ready and efficient.