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At Confluent, we’re committed to building the world's leading data streaming platform, which gives you the ability to stream, connect, process, and govern all of your data, and make it available wherever it’s needed—however it’s needed—in real time. Today, we're excited to announce the release of Confluent Platform 7.9! This release builds upon Apache Kafka 3.9, reinforcing our core capabilities as a data streaming platform.

Our Q1 Confluent Cloud launch comes to you from Current Bengaluru, where data streaming industry experts have gathered to showcase how real-time streaming with Apache Kafka, Apache Flink, and Apache Iceberg is enabling generative artificial intelligence (AI) use cases and helping their organizations take innovation to the next level.

We are proud to announce the release of Apache Kafka 4.0. This release contains many new features and improvements. This blog post will highlight some of the more prominent ones. For a full list of changes, be sure to check the release notes.

Toxic player behavior will drive players away from an otherwise successful game. While friendly banter and trash talk can build camaraderie, context matters—as what’s okay among longtime friends might be harassment to a stranger. How can studios create a positive atmosphere for all while still allowing friends to have a little fun at each other’s expense?

In our 2024 Data Streaming Report, we surveyed 4,110 IT leaders about the pivotal role that data streaming plays in their businesses. Of the respondents, 91% indicated that data streaming platforms (DSPs) are critical or important for achieving their data-related objectives—a result that comes as no surprise. Most IT teams—from architecture and integration teams to application and data engineers—that are using Confluent’s DSP get it.

In our previous blog post, we explored how Confluent has evolved into a comprehensive data streaming platform (DSP). Now that we understand what a DSP is, let's address a key question: How does it deliver business value? When business stakeholders assess value, they typically look at how a solution might help drive benefits across three key areas: So how does a DSP support these key areas?

Can you delete a topic in Apache Kafka? The answer is yes—but the process depends on your Kafka configuration and the environment in which you are working (i.e., if it is self-managed, hosted in the cloud, or a fully managed Kafka service like Confluent Cloud).

Companies need to adapt quickly to stay ahead of their competitors. This is where data-driven agility becomes essential. By leveraging real-time data, businesses can immediately respond to market changes and confidently make informed decisions. This article will explain data-driven agility, how it works, and why it’s a valuable approach for any organization. At its core, data-driven agility involves using live data to predict and respond to changes.

Easy access to data is a key part of any successful business strategy. Accessing, sharing, and analyzing data quickly helps organizations make smarter decisions, streamline operations, and stay competitive. However, many businesses face a significant challenge: they collect vast amounts of data from different sources yet often lack the right tools, processes, or infrastructure to make that data easy to access and use across the company.

Relying on intuition alone isn’t enough to stay ahead of the game in today’s fast-paced business environment. Success now comes from smart, data-driven decision-making backed by real-time insights and analytics. With stream processing and modern analytics platforms, businesses can collect, process, and analyze information as it happens, giving them a clear edge.