Executive SummaryUpdated on Dec 17, 2024
Azure Stream Analytics and Apache Spark Streaming are key players in the real-time analytics sector. Azure Stream Analytics seems to have the upper hand due to its seamless integration with Azure services and strong real-time capabilities.
Features: Azure Stream Analytics offers easy integration with Azure services, minimal setup requirements, and high scalability. Key features include IoT hubs, Blob storage, and data streaming to Power BI. Apache Spark Streaming supports multiple programming languages, handles large-scale data with low latency, and boasts an open-source nature for diverse project flexibility.
Room for Improvement: Azure Stream Analytics is limited by its Azure-specific nature, lacks flexibility in query customization, and has issues with Power BI integrations and pricing transparency. Apache Spark Streaming struggles with memory management and latency, lacking real-time capabilities compared to alternatives. Its setup is complex and not cloud-native, hindering cloud migrations and needing event handling and cost improvements.
Ease of Deployment and Customer Service: Azure Stream Analytics is available on public and private clouds, with solid Microsoft support, although experiences vary depending on subscription plans. Apache Spark Streaming can be deployed in various environments, relying on community forums for support, which may challenge users unfamiliar with its ecosystem.
Pricing and ROI: Azure Stream Analytics tends to be more expensive than open-source options like Apache Spark Streaming, with pricing based on streaming units causing confusion. Apache Spark Streaming's open-source nature offers an affordable alternative. Both solutions deliver decent ROI, with Azure showcasing quick deployments and Spark benefiting from its no-cost availability.
To learn more, read our detailed
Apache Spark Streaming vs. Azure Stream Analytics Report (Updated: December 2024).
