Easily manage real-time streaming data on AWS, Azure, & GCP with CDP.

Cloudera Data Platform (CDP) simplifies data collection and streaming with easy-to-use cloud services available on AWS, Azure, and Google Cloud Platform (GCP). Hybrid use cases are easier to deploy due to the simplicity of CDP cluster management and an experience consistent with on-premises DataFlow tools.

Deployment of flow management and streams processing clusters with CDP, accessed through the simple, yet powerful Data Hub service takes just minutes in the cloud and eliminates complex, time-consuming infrastructure planning and management.

DataFlow for Data Hub also deliver enterprise scale and security, combining the innovation and power of Apache NiFi, Kafka, and Flink with Cloudera SDX for consistent security and governance across public and hybrid clouds.

DataFlow for Data Hub cloud services

  • Flow Management
  • Streams Messaging
  • Streaming Analytics

Flow Management

Spin-up NiFi clusters to quickly orchestrate data collection, distribution, and transformation. 

Flow Management on Data Hub offers a simple visual UI for building sophisticated data ingestion, transformation, and enrichment requirements across a variety of streaming data sources and targets. This enables you to quickly ingest streaming data from devices, enterprises applications, partner systems, and cloud applications at capacities over 1 billion events per second.

Streams Messaging

Extend your on-premises Kafka to the public cloud to buffer and scale voluminous data streams. 

Streams Messaging on Data Hub enables enterprises to ingest, buffer, and scale massive volumes of real-time data to serve on-premises and cloud applications. Primarily powered by Apache Kafka, the Streams Messaging capabilities enable real-time data access to a wide range of applications such as analytic engines, data lakes, and time series databases.

Streaming Analytics

Spin-up Apache Flink clusters to process Kafka or NiFi streams to deliver real-time analytics in the cloud.

Streaming Analytics on Data Hub employs the latest generation of low-latency stream processing and analytic engines that address the requirements of real-time insights and predictive analytics. Powered by Apache Flink, it helps to democratize streaming analytics across the enterprise to deliver better business outcomes, faster.

Key features

Extend your on-premises streaming capabilities with Cloudera DataFlow on the public cloud. With Cloudera Data Hub, it is easy to spin up NiFi, Kafka, or Flink clusters on AWS, Azure, and GCP in a matter of minutes.

Accelerate development of data pipelines with Flow Management on Data Hub. Move any data to and from the cloud with Apache NiFi with its no-code interface and 300+ prebuilt processors. NiFi registry versions the data flows for governance and deployment.

Streams Messaging on Data Hub delivers utmost scalability by buffering volumes of incoming data for other cloud and enterprise applications to subscribe. Powered by Apache Kafka as the messaging platform, it is supported by Schema Registry and Streams Messaging Manager.

Streaming Analytics on Data Hub helps businesses to democratize streaming analytics across the firm and improves detection and response to critical events that deliver better business outcomes. Apache Flink delivers low latency and stateful processing of high volume data streams.

Manage high-volume, high-velocity data from your on-premises environments to public clouds easily with Data Hub. DataFlow’s comprehensive capabilities make it simple to ingest, buffer, and analyze streaming data across multi-cloud and hybrid cloud architectures.

With different DataFlow clusters, you can set up a distributed data management architecture that can span from edge to cloud. Integration with Cloudera SDX gives DataFlow the advantage of seamless security and governance across all your data-in-motion and data-at-rest locations.

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Cloudera DataFlow for Data Hub


Extend your on-premises streaming to the public cloud


How to connect NiFi to Kafka in Data Hub on CDP

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