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Kafka

Current '23 Keynote: Streaming into the Future - The Evolution & Impact of Data Streaming Platforms

Jay Kreps (Confluent Co-Founder and CEO), Shaun Clowes (Confluent CPO), and data streaming leaders from organizations like NASA, Warner Brothers, and Notion explore the past, present, and future of data streaming. They will address two key questions: how can organizations integrate data across their applications to deliver better experiences, and how can they embed data and analytics into every part of the business to drive better decision-making?

Top 6 Reasons to Modernize Legacy Messaging Infrastructure

Traditional messaging middleware like Message Queues (MQs), Enterprise Service Buses (ESBs), and Extract, Transform and Load (ETL) tools have been widely used for decades to handle message distribution and inter-service communication across distributed applications. However, they can no longer keep up with the needs of modern applications across hybrid and multi cloud environments for asynchronicity, heterogeneous datasets and high volume throughput.

Practical Data Mesh: Building Decentralized Data Architectures with Event Streams

Why a data mesh? Predicated on delivering data as a first-class product, data mesh focuses on making it easy to publish and access important data across your organization. An event-driven data mesh combines the scale and performance of data in motion with product-focused rigor and self-service capabilities, putting data at the front and center of both operational and analytical use-cases.

Confluent unveils Apache Flink® on Confluent Cloud, making it easier to build real-time applications with stream processing on a unified platform

Confluent launches the industry's only serverless, cloud-native Flink service to simplify building high-quality, reusable data streams. Confluent expands Stream Governance capabilities with Data Portal, so teams can easily find all the real-time data streams in an organisation. New Confluent Cloud Enterprise offering lowers the cost of private networking and storage for Apache Kafka.

Introducing Confluent Cloud for Apache Flink

In the first three parts of our Inside Flink blog series, we discussed the benefits of stream processing, explored why developers are choosing Apache Flink® for a variety of stream processing use cases, and took a deep dive into Flink's SQL API. In this post, we'll focus on how we’ve re-architected Flink as a cloud-native service on Confluent Cloud. However, before we get into the specifics, there is exciting news to share.

Deliver Intelligent, Secure, and Cost-Effective Data Pipelines

The Q3 Confluent Cloud Launch comes to you from Current 2023, where data streaming industry experts have come together to share insights into the future of data streaming and new areas of innovation. This year, we’re introducing Confluent Cloud’s fully managed service for Apache Flink®, improvements to Kora Engine, how AI and streaming work together, and much more.

Lenses 5.3: Robust Kafka with single click topic backup/restore

Navigating the intricacies of Apache Kafka just got a lot more intuitive. With Lenses 5.3 we bring you peace of mind, regardless of where you are in your Kafka journey. Our newest release is all about smoothing out the bumps, and making sure you're equipped to handle Kafka's challenges with confidence. Here's a sprinkle of what's in store, ahead of our big 6.0 release later this year.

A single-click Kafka topic backup experience

We like to reduce the most mundane, complex and time-consuming work associated with managing a Kafka platform. One such task is backing up topic data. With a growing reliance on Kafka for various workloads, having a solid backup strategy is not just a nice-to-have, but a necessity. If you haven’t backed up your Kafka and you live in fear of disaster striking, worry no more.