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Summary: This is a summary of an article originally published by The New Stack. Read the full original article here →
The challenge is clear: How to offer real- or near real-time access to data that is continually refreshed across a number of different distributed environments. With different types of data streaming from various sources such as multicloud and on-premises environments, the data, often in shared digital layers such as so-called digital information hubs (DIHs), must be updated asynchronously.
Not to be confused with Kubernetes clusters, Confluent clusters provide a platform to set data in motion whereas Kubernetes clusters provide a platform to run applications and other platforms, Knepper explained. “A Confluent cluster can move data between many different applications and regions. A Kubernetes cluster can host those applications — and can even host a Confluent cluster,” Knepper said. “Our customers who choose to self-host their Confluent clusters can leverage Confluent for Kubernetes to run Confluent Platform on top of their Kubernetes clusters.”
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