Confluent Launches Connect with Confluent, Enabling Partners to Supercharge Growth and Customer Innovation with Data Streaming

Confluent, Inc. (NASDAQ:CFLT), the data streaming pioneer, today announced the Connect with Confluent technology partner program. The program enables partners to bring fully managed data streams directly to their customers through native integrations with Confluent Cloud. It also provides access to Confluent’s leading expertise for technical, sales, and marketing support to amplify go-to-market efforts and ensure customer success at every stage. By joining the program, partners tap into an ecosystem of technologies fueled by data streams and unlock massive potential for what’s possible on their platforms.

“When companies can harness streams of real-time data from previously siloed teams and applications across their business, it creates a powerful network effect that opens new avenues for growth and innovation,” Erica Schultz, President of Field Operations, Confluent. “As technology partners bring Confluent data streams directly into their platforms, they unlock potential for more cutting edge, real-time applications to be developed on their platform.”

Business is conducted in real time and companies need their customer experiences and operations to reflect that. This need for real-time data has cemented data streaming as a critical business requirement. According to the 2023 Data Streaming Report, 89% of technology leaders say investments in data streaming are important, while 44% cite the technology as a top strategic priority for their business. This shift increases pressure on technology providers to support low latency data movement—skipping data-at-rest pit stops in cloud storage buckets and enabling development of end-to-end real-time experiences their customers expect.

To solve this problem, developers often turn to Apache Kafka, the open source data streaming platform used by more than 75% of the Fortune 500. However, when partners build integrations with open source Kafka, they put extra burdens on their customers to develop and deploy Kafka clusters, which must be manually secured, governed, and managed as they scale. Customers are then responsible for individually integrating all of their data into this cluster. These operational burdens come at the expense of customers actually building and deploying anything new on the partner’s platform.