Microsoft today announced the general availability of Azure Data Lake Analytics, Azure Data Lake Store along with HD Insights. In case you are not familiar with the terms, Azure Data Lake services are all about Big Data.
Azure Data Lake ushers in a new era of productivity for big data developers and scientists. It enhances their productivity by saving time mostly spent on infrastructure planning, and writing, debugging, & optimizing code with primitive tooling. The traditional approach lacks the built-in cognitive capabilities like keyphrase extraction, sentiment analysis, image tagging, OCR, face detection, and emotion analysis.
The Azure Data Lake services enable you to securely store all your data centrally in a “no limits” data lake, and run on-demand analytics that instantly scales to your needs.
Our state-of-the-art development environment and rich and extensible U-SQL language enable you to write, debug, and optimize massively parallel analytics programs in a fraction of the time of existing solutions.
With Azure Data Lake
- Azure Data Lake Store – the first cloud Data Lake for enterprises that is secure, massively scalable and built to the open HDFS standard. With no limits to the size of data and the ability to run massively parallel analytics, you can now unlock value from all your unstructured, semi-structured and structured data.
- Azure Data Lake Analytics – the first cloud analytics job service where you can easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python and .NET over petabytes of data. It has rich built-in cognitive capabilities such as image tagging, emotion detection, face detection, deriving meaning from text, and sentiment analysis with the ability to extend to any type of analytics. With Azure Data Lake Analytics, there is no infrastructure to manage, and you can process data on demand, scale instantly, and only pay per job.
- Azure HDInsight – the only fully managed cloud Hadoop offering that provides optimized open source analytic clusters for Spark, Hive, Map Reduce, HBase, Storm, Kafka and R-Server backed by a 99.9% SLA. Today, we are announcing the general availability of R Server for HDInsight to do advanced analytics and predictive modelling with R+Spark. Further, we are introducing the public preview of Kafka for HDInsight, now the first managed cluster solution in the cloud for real-time ingestion with Kafka.
You can read more about the services here
