In this blog we’ll discuss the concept of structured streaming and also how to build a data ingestion path directly using Azure Databricks enabling the streaming of data in near-real-time.
Hello SIGMOD attendees! Welcome to Houston, and to what is shaping up to be a great conference.
It has been three months since we closed on the acquisition of Avere Systems. Since that time, we’ve been hard at work integrating the Avere and Microsoft families, growing our presence in Pittsburgh and meeting with customers and partners at The National Association of Broadcasters Show.
With Azure Data Factory (ADF) visual tools, we listened to your feedback and enabled a rich, interactive visual authoring and monitoring experience. It allows you to iteratively create, configure, test, deploy and monitor data integration pipelines without any friction.
Apache Kafka has changed the way we look at streaming and logging data, and now Azure provides tools and services for streaming data into your big data pipeline in Azure.
Azure Stream Analytics is a serverless PaaS service in Azure to run real-time analytics on fast moving streams of data. Today, we are excited to announce several new features in Azure Stream Analytics.
Secure credential management is essential to protect data in the cloud.
There is increasingly a need among users to develop and debug their Extract Transform/Load (ETL) and Extract Load/Transform (ELT) workflows iteratively. Now, Azure Data Factory (ADF) visual tools allow you to do iterative development and debugging.
The General Data Protection Regulation (GDPR) officially goes into effect on May 25. Will your organization be ready?
Azure Data Factory (ADF) visual tools public preview was announced on January 16, 2018. With visual tools, you can iteratively build, debug, deploy, operationalize and monitor your big data pipelines.
