Azure Stream Analytics vs Cloudera DataFlow comparison

Azure Stream Analytics is a robust real-time analytics service that has been designed for critical business workloads. Users are able to build an end-to-end serverless streaming pipeline in minutes. Utilizing SQL, users are able to go from zero to production with a few clicks, all easily extensible with unique code and automatic machine learning abilities for the most advanced scenarios.

Azure Stream Analytics has the ability to analyze and accurately process exorbitant volumes of high-speed streaming data from numerous sources at the same time. Patterns and scenarios are quickly identified and information is gathered from various input sources, such as social media feeds, applications, clickstreams, sensors, and devices. These patterns can then be implemented to trigger actions and launch workflows, such as feeding data to a reporting tool, storing data for later use, or creating alerts. Azure Stream Analytics is also offered on Azure IoT Edge runtime, so the data can be processed on IoT devices.

Top Benefits

• User friendly: Azure Stream Analytics is very straightforward and easy to use. Out of the box and with a few clicks, users are able to connect to numerous sources and sinks, and easily develop an end-to-end pipeline. Stream Analytics can easily connect to Azure IoT Hub and Azure Event Hub for streaming ingestion, in addition to connecting with Azure Blob storage for historical data ingestion.
  
  
• Flexible deployment: For low-latency analytics, Azure Stream Analytics can run on Azure Stack or IoT edge. For large-scale analytics, the solution can run in the cloud. Azure Stream Analytics uses the same query language and tools for both the cloud and the edge, facilitating an easier process for developers to design exceptional hybrid architectures for streaming processes.
  
  
• Cost-effective: With Azure Stream Analytics, users only pay for the streaming units they consume; there are no upfront costs. Users can easily scale up or down as needed; there is no commitment or cluster provisioning.
  
  
• Trustworthy: Azure Stream Analytics guarantees event processing to be 99.99% available with a minute level of granularity. Azure Stream Analytics has embedded recovery capabilities and checkpoints to keep things running smoothly at all times. Events are never lost with Azure Stream Analytics at-least once delivery of events and exactly one event processing.

Reviews from Real Users

“Azure Stream Analytics is something that you can use to test out streaming scenarios very quickly in the general sense and it is useful for IoT scenarios. If I was to do a project with IoT and I needed a streaming solution, Azure Stream Analytics would be a top choice. The most valuable features of Azure Stream Analytics are the ease of provisioning and the interface is not terribly complex.” - Olubisi A., Team Lead at a tech services company.

“It's used primarily for data and mining - everything from the telemetry data side of things. It's great for streaming and makes everything easy to handle. The streaming from the IoT hub and the messaging are aspects I like a lot.” - Sudhendra U., Technical Architect at Infosys

Cloudera DataFlow (CDF) is a comprehensive edge-to-cloud real-time streaming data platform that gathers, curates, and analyzes data to provide customers with useful insight for immediately actionable intelligence. It resolves issues with real-time stream processing, streaming analytics, data provenance, and data ingestion from IoT devices and other sources that are associated with data in motion. Cloudera DataFlow enables secure and controlled data intake, data transformation, and content routing because it is built entirely on open-source technologies. With regard to all of your strategic digital projects, Cloudera DataFlow enables you to provide a superior customer experience, increase operational effectiveness, and maintain a competitive edge.

With Cloudera DataFlow, you can take the next step in modernizing your data streams by connecting your on-premises flow management, streams messaging, and stream processing and analytics capabilities to the public cloud.

Cloudera DataFlow Advantage Features

Cloudera DataFlow has many valuable key features. Some of the most useful ones include:

• Edge and flow management: Edge agents and an edge management hub work together to provide the edge management capability. Edge agents can be managed, controlled, and watched over in order to gather information from edge hardware and push intelligence back to the edge. Thousands of edge devices can now be used to design, deploy, run, and monitor edge flow apps. Edge Flow Manager (EFM) is an agent management hub that enables the development, deployment, and monitoring of edge flows on thousands of MiNiFi agents using a graphical flow-based programming model.

• Streams messaging: The CDF platform guarantees that all ingested data streams can be temporarily buffered so that other applications can use the data as needed. This makes it possible for a business to scale efficiently, as data streams from thousands of origination points start to grow to petabyte sizes. To achieve IoT-scale, streams messaging allows you to buffer large data streams using a publish-subscribe strategy.

• Stream analytics and processing: The third tenet of the CDF platform is its capacity to analyze incoming data streams in real time and with minimal latency, providing actionable intelligence in the form of predictive and prescriptive insights. This stage is essential to completing the Data-in-Motion lifecycle for an enterprise because there is only a use in absorbing all real-time streams if something useful is done with them in the moment to benefit your company.

• Shared Data Experience (SDX): The most crucial component that transforms CDF into a genuine platform is Cloudera Data Platform's SDX. It is a powerful data fabric that offers the broadest possible deployment flexibility and guarantees total security, governance, and control across infrastructures. You get a single experience for security (with Apache Ranger), governance (with Apache Atlas), and data lineage from edge to cloud because all the CDF components seamlessly connect with SDX.

Cloudera DataFlow Advantage Benefits

There are many benefits to implementing Cloudera DataFlow . Some of the biggest advantages the solution offers include:

• Completely open source: Invest in your architecture with confidence, knowing that there will be no vendor lock-in.

• More than 300 pre-built processors: This is the only product that provides edge-to-cloud connection this comprehensive as well as a no-code user experience

• Integrated data provenance: The market's only platform that offers out-of-the-box, end-to-end data lineage tracking and provenance across MiNiFi, NiFi, Kafka, Flink, and more.

• Multiple stream processing engines to choose from: Supports Spark structured streaming, Kafka Streams, and Apache Flink for real-time insights and predictive analytics.

• Hundred of Kafka consumers: Cloudera has hundreds of satisfied customers who receive exceptional support for their complex Kafka implementations.

• Use cases for edge IoT: IoT data from thousands of endpoints may be easily collected, processed, and managed from the edge to the cloud with a multi-cloud/hybrid cloud strategy.

• Hybrid/multi-cloud approach: Choose a flexible deployment option for your streaming architecture that spans across edge, on-premises, and various cloud environments with ease thanks to the power of CDP.