Unlocking Real-Time Insights: Streaming Azure Event Hub Data to Snowflake

Streaming data from Kafka, Azure Event Hubs, etc. is a common practice in modern data processing and analytics. These platforms are designed to handle large volumes of real-time data and provide a reliable way to ingest and process streaming data. Event Hub is commonly used in scenarios where data needs to be processed and analyzed in near real-time, such as monitoring, analytics, and event-driven applications. Getting data out of Azure Event Hub and into a database for near real-time insight can present several challenges, primarily related to data processing, transformation, infrastructure management, and monitoring. Many Snowflake customers sink data in blob storage, from Azure Event Hub, before loading it into Snowflake, which increases the overall latency. Low latency is essential for various applications because it directly impacts the responsiveness, and user experience; for example, Clickstream data latency can pose several challenges such as delayed insights and missed opportunities. To overcome these challenges Snowflake offers various features such as <a href="https://docs.snowflake.com/en/user-guide/data-load-snowpipe-streaming-overview" rel="noopener ugc nofollow" target="_blank">Snowpipe Streaming</a>, <a href="https://docs.snowflake.com/en/user-guide/kafka-connector-overview" rel="noopener ugc nofollow" target="_blank">Kafka Connector</a>, Snowpark Container Services (Private Preview in AWS), and <a href="https://docs.snowflake.com/en/developer-guide/streamlit/about-streamlit" rel="noopener ugc nofollow" target="_blank">Streamlit in Snowflake</a> (Public Preview in AWS), which help you build a data pipeline and monitor it without managing any infrastructure i.e. all parts of managed service. <a href="https://medium.com/snowflake/unlocking-real-time-insights-streaming-azure-event-hub-data-to-snowflake-4c8516539b52">Website</a>