We are excited to announce that the capability to output to Azure Data Lake Store, a hyper-scale repository for big data analytics workloads from Azure Stream Analytics is now Generally Available.
This integration further advances the ease of enablement of a Lambda architecture where the data that is subjected to real time stream analytics is also stored and then subjected to offline batch processing to unlock powerful insights. A large number of batch processing possibilities are enabled by virtue of Data Lake Store’s integration with Azure Data Lake Analytics, Azure HDInsight, Microsoft Revolution-R Enterprise, and Hadoop distributions from various industry-leading providers.
Azure Data Lake Store is built for supporting the storage needs of big data analytics systems that require massive throughput to query and analyze petabytes of data. The capabilities will be highly useful as data to be analyzed continues to grow exponentially, especially in stream scenarios like IoT. It also provides low latency read/write accesses and high throughput for data from typical Stream Analytics scenarios such as real-time event stream analysis, real time web log analysis, and analytics on Internet of Things (IoT) sensor data.
The ability to output to Azure Data Lake Store from Stream Analytics can be enabled by selecting “Data Lake Store” as the output choice when adding a new output:
Additional details on outputting to Data Lake Store from Stream Analytics are covered here.
— Sam Chandrashekar, Program Manager