"Confluent has been instrumental in the company’s ability to scale. It’s not unusual to have 25 million concurrent users for a live match, and on a daily basis seven to eight terabytes of data come into the platform. According to Disney+ Hotstar, powering so many use cases at this scale …

“When we're using services like Confluent for data delivery, we don't need to think about it. It just gets delivered.”

“Based on previous interactions, location, and past orders, the system can promote specific products and provide bespoke offers to customers."

"We chose event-driven architecture as the core of our platform. For which we needed a messaging service that gave us all the guarantees not to mention that it had to be extremely scalable, highly available, and simple to use."

"Real-time inventory accuracy is just the foundation for much more than just inventory management; it enables retailers to improve post sales and supply chain processes as well as customer engagement and the customer experience. And beyond retail, the real-time asset tracking and supply chain management solutions we’ve built with Kafka …

"The level of credibility that Confluent has built in terms of modern, scalable and flexible stream processing does much of our blocking and tackling for us."

"We had no technologies to replace or augment because we’d never used event streaming technology before. Some of our members from different groups had experience handling Apache Kafka, but they weren’t part of the bigger project to build a data streaming platform. Confluent had an ability to immediately offer enterprise-level …

"With Kafka, we can liberate data from our heritage systems and combine it with real-time signals from our customers to deliver a hyper-personalized experience. For example, if our clickstream data shows a customer lingering over a product they looked at in the past, we can push a voucher to them …

"Our internal platform is totally based on Kafka communication between all the pillars, so it’s like a nervous system for us."

“We shouldn’t care where the data sits. We should be able to share and move data seamlessly between environments. Streaming is the key. Otherwise you’re copying and shipping data and it’s a moment in time. And our strategy based on what we’re doing with Confluent Kafka is saying ‘the moment …

"When we think of a better healthcare ecosystem, we really need to think about the opportunity to exchange data in a seamless way, where all participants can freely integrate that data to help drive the outcomes and the experience within their organizations."

"With our Kafka-backed data pipeline, we are able to support our partners, who every year create more services, more features, more data instrumentation, and even more granular data than the year before."

"Confluent Platform and Apache Kafka, by enabling us to build and deploy real-time event-driven systems for credit scoring, have helped BRI become the most profitable bank in Indonesia."

“To have data streaming implemented at a global scale at L'Oréal called for a platform that’s reliable, can auto-scale depending on our need and can cater to our future growth—all while ensuring we get the utmost support we need. That’s why we invested in Confluent.”

”With Confluent, it was easier for the team to set up, configure, and scale to support the increasing volume and throughput of the source systems we’re generating. This allowed us to build more microservices that are processing and aggregating data to deliver fit-for-purpose topics.”