Azure Event Hubs enables you to stream millions of events per second from any source using Kafka, AMQP or HTTPS protocols. Using Event Hubs capture feature, you can load real-time streaming data to data lakes, warehouses, and other storage services, so that they can be processed or analyzed by analytics services.
Today we are excited to announce the preview of Apache Parquet capturing support in Azure Event Hubs.
Why Apache Parquet for big data analytics?
Apache Parquet is column-oriented storage format that is designed for efficient data storage and retrieval. It’s open source and is not tied to any processing framework, data model or programming language. Parquet is ideal for storing any kind of big data and is built to support efficient compression and encoding schemes.
Capture streaming data in Parquet format using Event Hubs
Using Azure Event Hubs, no code editor for event processing, you can automatically capture streaming data in an Azure Data Lake Storage Gen2 account in Parquet format. The no code editor allows you to easily develop an Azure Stream Analytics job without writing a single line of code.
Once data is captured, any analytics service of your choice can process or analyze Parquet data.
Get Started Today
You can try out Apache Parquet capturing feature in Azure Event Hubs using the following links.
- To try out Parquet capturing feature, follow Capture data from Event Hubs in Parquet format.
- You can follow the tutorial on Capture Event Hubs data in Parquet format and analyze with Azure Synapse Analytics.
- To learn more about no code editor in Event Hubs for event stream processing, check out No code stream processing using Azure Stream Analytics (Preview).
