[Webinaire] La reprise après sinistre des systèmes basés sur Kafka | Inscrivez-vous dès maintenant
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...
Learn how the latest innovations in Kora enable us to introduce new Confluent Cloud Freight clusters, which can save you up to 90% at GBps+ scale. Confluent Cloud Freight clusters are now available in Early Access.
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.
When a company becomes overreliant on a centralized database, a world of bad things start to happen. Queries become slow, taxing an overburdened execution engine. Engineering decisions come to a […]
The combination of streaming machine learning (ML) and Confluent Tiered Storage enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache […]
A preview of Confluent Tiered Storage is now available in Confluent Platform 5.4, enabling operators to add an additional storage tier for data in Confluent Platform. If you’re curious about […]
I am pleased to announce the release of Confluent Platform 5.4. Like any new release of Confluent Platform, it’s packed with features. To make them easier to digest, I want […]
Netflix spent an estimated $15 billion to produce world-class original content in 2019. When stakes are so high, it is paramount to enable our business with critical insights that help […]
Now that we’ve learned about the processing layer of Apache Kafka® by looking at streams and tables, as well as the architecture of distributed processing with the Kafka Streams API […]
Part 2 of this series discussed in detail the storage layer of Apache Kafka: topics, partitions, and brokers, along with storage formats and event partitioning. Now that we have this […]
Part 1 of this series discussed the basic elements of an event streaming platform: events, streams, and tables. We also introduced the stream-table duality and learned why it is a […]
This four-part series explores the core fundamentals of Kafka’s storage and processing layers and how they interrelate. In this first part, we begin with an overview of events, streams, tables, […]
This article shows how you can offload data from on-premises transactional (OLTP) databases to cloud-based datastores, including Snowflake and Amazon S3 with Athena. I’m also going to take the opportunity […]
Following Google’s announcement to provide leading open source services with a cloud-native experience by partnering with companies like Confluent, we are delighted to share that Confluent Cloud is now available […]
When KSQL was released, my first blog post about it showed how to use KSQL with Twitter data. Two years later, its successor ksqlDB was born, which we announced this […]
With Confluent Platform 5.3, we are actively embracing the rising DevOps movement by introducing CP-Ansible, our very own open source Ansible playbooks for deployment of Apache Kafka® and the Confluent […]
The amount of time it takes for a message to move through a system plays a big role in the performance of distributed systems like Apache Kafka®. In Kafka, the […]