- Apache Spark for Azure HDInsight – an open source framework for
processing large data analytic applications. Apache Spark in the cloud is faster
and is commonly used for tasks within an Apache HDFS (Hadoop Distributed
File System). Cost effective, no hardware or software to purchase and fully
integrates with intelligence business tools from trusted partners. - Apache Storm for HDInsight – distributed open-source, fault-tolerant,
event-processing solution for large streams of fast data. Easy, cost-effective, no
hardware or software to buy or configure, configuration tools of your choice and
fully integrated with Visual Studio. - R Server for HDInsight – R Server is a combination of R analytics software
(enterprise-scale) and the power of Apache Spark and Hadoop. Train accurate
models to provide better predictions, working with open-source R-language. - Data Catalog – a metadata catalog that makes it easy to discover data assets. A
managed service, it allows you to register, discover, enrich, understand and
consume data sources, working with the data tool you choose. Use the data in the
tools you want it in and gain more value from it – less time looking for data =
more time using it. - Azure Data Lake Storage – a scalable, cost-effective solution for big data
analytics, combining economy and scale with the power from a high-performance
file system. Extends Blob Storage capabilities; store the data once and access it
via existing file system interfaces and Blob storage with no changes to
programming. - Azure Data Explorer – a fast and easy service for indexing and querying large
amounts of data to build near real-time solutions for analytics. Identify patterns,
trends and anomalies in any type of data, structured, unstructured or semi-
structured.
lvitn
(lvitn)
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