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Apache Flink
Data Products, Data Contracts, and Change Data Capture
Change data capture is a popular method to connect database tables to data streams, but it comes with drawbacks. The next evolution of the CDC pattern, first-class data products, provide resilient pipelines that support both real-time and batch processing while isolating upstream systems...
Unlock Cost Savings with Freight Clusters–Now in General Availability
Confluent Cloud Freight clusters are now Generally Available on AWS. In this blog, learn how Freight clusters can save you up to 90% at GBps+ scale.
Contributing to Apache Kafka®: How to Write a KIP
Learn how to contribute to open source Apache Kafka by writing Kafka Improvement Proposals (KIPs) that solve problems and add features! Read on for real examples.
Effortless Stream Processing on Any Cloud – Flink Actions, Terraform Support, and Multi-Cloud Availability
Several key new features have been added to Confluent Cloud for Apache Flink this year including Topic Actions, Terraform support, and expansion into GCP and Azure. Let's take a look at these enhancements and how they empower users to harness the full potential of streaming data.
Build Streaming Apps Quickly with Flink SQL Workspaces
In this blog post, we will provide an overview of Confluent's new SQL Workspaces for Flink, which offer the same functionality for streaming data that SQL users have come to expect for batch-based systems.
Announcing Apache Flink 1.18
The Apache Flink PMC is pleased to announce the release of Apache Flink 1.18.0. As usual, we are looking at a packed release with a wide variety of improvements and new features. Overall, 174 people contributed to this release completing 18 FLIPS and 700+ issues.
Introducing Confluent Cloud for Apache Flink
As of today, Confluent Cloud for Apache Flink® is available for preview in select regions on AWS. In this post, learn how we’ve re-architected Flink as a cloud-native service on Confluent Cloud.
Dataflow Programming with Apache Flink and Apache Kafka
Learn how to build a Java pipeline that consumes clickstream data from Apache Kafka®. Consuming clickstreams is something that many businesses have a use for and it can also be generalized to consuming other types of streaming data.
Your Guide to Flink SQL: An In-Depth Exploration
Dive into Flink SQL, a powerful data processing engine that allows you to process and analyze large volumes of data in real time. We’ll cover how Flink SQL relates to the other Flink APIs and showcase some of its built-in functions and operations with syntax examples.
Flink in Practice: Stream Processing Use Cases for Kafka Users
Apache Flink can be used for multiple stream processing use cases. In this post we show how developers can use Flink to build real-time applications, run analytical workloads or build real-time pipelines.
Stream Processing Simplified: An Inside Look at Flink for Kafka Users
Learn why stream processing is such a critical component of the data streaming stack, why developers are choosing Apache Flink as their stream processing framework of choice, and how to use Flink with Kafka.