Introducing Streamhouse: the open data architecture for AI | Learn More
New industry initiative establishes an open category for data architectures that power real-time applications and AI agents
Learn how to migrate to Confluent Cloud in hours using Confluent’s open source Kafka Copy Paste tool. Get an in-depth introduction to the KCP tool and a walk-through of the four steps of migrating from MSK to Confluent Cloud using the tool.
ConfluentのAI開発者向けツールが一般提供(GA)されました。これには、オープンソースのローカルMCP Server、マネージドのMCP Server、およびAgent Skillsが含まれます。これらを組み合わせることで、AIコーディングアシスタントはお客様のストリーミングプラットフォームに直接アクセスできるようになります。つまり、プラットフォーム上で処理を実行するためのツールと、正しく構築するためのドメイン知識が提供されました。
To the developer or architect seeking to provide their business with as much value as possible, what is the best way to start working with data in motion? Choosing Apache […]
Stream processing has become an important part of the big data landscape, a new programming paradigm bringing asynchronous, long-lived computations to unbounded data in motion. But many people still think […]
This blog post is the fourth in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on removing […]
This blog post is the third in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on inspecting […]
This blog post is the second in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. This blog post focuses […]
Managing Apache Kafka® clusters can be tricky sometimes. To solve this problem, Confluent Control Center helps you easily manage and monitor your clusters and interact with other Confluent components, such […]
For a modern, software-defined business, a platform for data in motion is critical to connecting every part of a vast digital architecture across an organization to harness the flow of […]
What if I told you there is a query your database can’t answer? That would probably surprise you. With decades of effort behind them, databases are one of the most […]
This is part two in a blog series on streaming a feed of AIS maritime data into Apache Kafka® using Confluent and how to apply it for a variety of […]
One of the canonical examples of streaming data is tracking location data over time. Whether it’s ride-sharing vehicles, the position of trains on the rail network, or tracking airplanes waking […]
We’re pleased to announce ksqlDB 0.18.0! This release includes pull queries on table-table joins and support for variable substitution in the Java client and ksqlDB’s migration tool. We’ll step through […]
When self-managing Confluent, provisioning and configuring Apache Kafka® deployments along with the rest of the Confluent components involves many hurdles, such as managing infrastructure, installing software, and configuring security. And […]
Apache Kafka® applications run in a distributed manner across multiple containers or machines. And in the world of distributed systems, what can go wrong often goes wrong. This blog post […]
When it comes to launching your next app with data in motion, few things pose the same risk to going live as meeting requirements for data security and compliance. Doing […]