141 Confluent Testimonials

"With Confluent, we have confidence in our Kafka deployment. Confluent engineers not only provide us with support, but they also share with us their deep knowledge of Kafka to help us make the most of our streaming use cases."

"With KSQL we can offer our enterprise customers and third-party service providers an accessible tool that lets anyone write simple SQL queries in order to prepare the data themselves, without getting engineers or developers involved, helping them achieve shorter time-to-market while also supporting more adaptive data models."

“With Confluent, we’ve been able to optimize our in-house Kafka-support resources by ~50% and redeploy our engineering and development talent to creating innovative and value-added features for our customers instead. Additionally, engaging Confluent gave us the peace of mind that comes with minimizing downtime and knowing that our Kafka systems are in the hands of one of the industry’s leading data-in-motion experts.”

"Availability of data is crucial, and having a fully managed platform for the data distribution lets us provide solutions to our customers at speed."

“Everything we do is in real time because batch processing is an old way of thinking. The longer your data waits, the less value it has. So, as data comes through, you need to be able to act on it, or enrich it quickly. Confluent enables this for us.”

“The expectation these days is that banks should always be available. Customers constantly want real-time experiences. One of the best ways to facilitate that is by leveraging a platform like Confluent.”

“The strength of the engineering team at Ladder really lies in making a great customer experience and automating business processes, rather than running a Kafka cluster. Putting our data in motion with Confluent allows us to focus on differentiating Ladder with automated underwriting built around machine learning models fed by real-time data.”

”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.”

"Using Kafka and Confluent, Walmart has initiated a digital transformation and modern omnichannel experience that allows customers to interact with Walmart.com seamlessly, order groceries online or in a mobile app, and either pick them up or have them delivered. Walmart’s investment in event streaming with Confluent has contributed to business innovation as well as company growth in the public market."

“Think of Confluent as a Swiss Army knife - it can do so many things in terms of data processing. We want to reduce the latency and increase data availability as much as we can, and we know we can scale even further with Confluent.”

“We’re expecting to increase our bottom-line revenue growth via data infrastructure cost savings of 20 to 30 percent, and we expect to greatly reduce the complexity of our data infrastructure thanks to Confluent.”

"We started with pay as you go, and had things up and running in about an hour. Confluent Cloud enabled us to defer the learning curve on running Kafka in-house. We currently don’t have the resources or bandwidth to host and manage clusters ourselves, so instead we have the experts on Kafka doing that for us.”

"With the ability to combine real-time results with historical events, Confluent is leading the charge in helping enterprises discover new services and modernize existing ones with the power of event streaming."

“With Flink, we now have the opportunity to shift left and do a lot of early data transformations and computation on our data before it reaches Snowflake. This will optimize our data processing costs to increase the amount of data we have available.”

“We're going up orders of magnitude on the volume of data that we want to transact over Confluent. By having a partner like Confluent, we can start generating value from our network at an unimaginable level today.”