Announcing the new Cloudera Streaming Analytics Community Edition.


What is Stream Processing & Analytics?

The Stream Processing and Analytics capabilities within Cloudera DataFlow (CDF), powered by Apache Flink, help businesses democratize real-time streaming analytics across the organization. This also improves detection and response to critical events that deliver business outcomes. With the advent of IoT and other streaming sources, unbounded data streams and events are constantly flowing into the enterprise. CDF’s stream-processing capabilities help analyze them in real time, identify key event patterns, and escalate key alerts based on predictive insights and actionable intelligence.

By enabling key stakeholders with access to real-time data, business decisions are made much faster and create the right business impact. Organizations can enable their analysts with such access with just SQL and not depend on developers to accelerate streaming analytics.

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Use cases

  • Fraud Detection
  • Log Analytics
  • Customer Analytics

Fraud detection

Prevent millions of dollars in loss due to financial fraud by detecting it proactively. 

Enterprises across retail, financial services, and other sectors struggle to protect customer data and prevent financial fraud from happening.  Cloudera DataFlow’s Streaming Processing and Analytics capabilities can process real-time streams of customer transactions, identify patterns, create predictive alerts and actionable intelligence to prevent potential fraud.

PT Bank Rakyat Indonesia: Using big data, AI, and ML to better understand customers

Achieved a 40 percent reduction in fraud.

Read the case study

Log analytics

Modernize your logging infrastructure to get real-time analytics.

Log data is increasingly valuable to enterprises. But IT organizations are struggling with effective log collection processes, distributing relevant information upstream, and generating key metrics. Cloudera DataFlow's Streaming Processing and Analytics capabilities help scale up log processing, deliver real-time insights across the firm, and significantly reduce operating costs.

Major airline: Enhancing customer experience with data-driven automation

Achieved a 50 percent data volume decrease by only paying for data streams to transmit once.

Read the case study

Customer analytics

Real-time customer analytics improves engagement, retention, and satisfaction.

Every organization needs real-time analytics to improve customer engagement but struggles to implement it due to an excessive volume of data. Cloudera DataFlow’s Stream Processing and Analytics enables customer analytics by processing massive amounts of data with subsecond latencies while detecting customer interactions and recommending better offerings in real time.

Shoppermotion: Reinventing in-store analytics to give brick-and-mortar retailers meaningful insight

9% retail category sales increase

Read the case study

Key features

Deliver real-time monitoring and parallel processing of millions of data points in subseconds. Distribute parallel processing, detecting patterns continuously without failure, to deliver predictive and prescriptive real-time insights.

Deliver real-time complex event processing across microservices, batch, and stream processing and analytics. Enable various windowing techniques to build sophisticated event-driven analytics, including the detection of mission-critical events that impact real-time decisions and automation.

Materialize results from a Streaming SQL query to a persistent view of the data that can be read through REST. Applications can use this mechanism to query streams of data without deploying database systems and without requiring any configuration or maintenance.

Ease of use and scalability encourage adoption across the enterprise. Data analysts, who normally build analytics with SQL, can use the same querying language to adopt streaming analytics, and streaming developers can build streaming analytics using SQL, Java, or Scala.

Set queries to handle event processing dynamically, base processing streams on state and time, and use watermarks to handle late and out-of-order delivery.

Use cases across industries and enterprises vary when it comes to real-time analytics. Cloudera supports three stream processing engines: Apache Flink, Spark Streaming, and Kafka Streams. Compare these engines for your use case in this whitepaper.

Deployment options

Democratize real-time stream processing and analytics across the organization in on-premises, public cloud, and hybrid cloud environments.

Streaming Analytics for Data Hub

  • Accelerate real-time stream processing with Apache Flink on hybrid cloud with Streaming Analytics for Data Hub
  • Choose your cluster size (S/M/L) and launch it across AWS, Azure or GCP
  • Extend the same on-premises user experience into the public cloud

CDP Private Cloud Base

  • Democratize streaming analytics across the firm with Apache Flink and SQL Stream Builder
  • Enable analysts and developers to create streaming analytics using SQL
  • Enrich data by joining a variety of data sources including streaming and batch sources

Get started

Product documentation

Read technical specifications, architecture, tutorials, and how-to articles about Apache Flink.

Learn more

CDP Data Hub pricing

Evaluate CDP Public Cloud pricing for Data Hub across various instance types and cloud providers.

Get the details

Flink on the cloud

Extend your streaming processing and analytics capabilities to the cloud with CDP Data Hub.

Watch a quick intro video

Streaming analytics resources

Get all the key assets to learn more about the power of real-time stream processing and analytics.

Access now

Cloudera Community on Flink

Connect with your peers, ask questions, troubleshoot, and learn more about Apache Flink.

Explore now


Read how Streaming SQL eases building queries against data streams for streaming analytics.

Download the whitepaper


Liberating real-time data access with the new Cloudera SQL Stream Builder


Modern stream processing using streaming SQL


Choose the right stream processing engine for your data needs


Cloudera Streaming Analytics

World-class training, support, & services

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