Big-Data and microsoft

The traditional data warehouse has reached a critical point, which requiring major business-driven changes to the system in place today.

Key reasons for the changes…

  • Volume and Velocity of data
  • Non-traditional data (Blogs, Social media, and Mobile gadgets)
  • Real time data expectation from customers

Adronics Inc partnering with Microsoft and ready to help organizations transition to a modern data warehouse with the Microsoft Analytics Platform System (APS), a no-compromise solution that unifies non-relational data from HDInsight, Microsoft’s 100-percent distribution of Hadoop based on the Hortonworks data Platform, with relational data from Microsoft SQL Server Parallel Data Warehouse (PDW), a massively parallel processing (MPP) relational data warehouse, into a single integrated appliance. APS provides tier-one performance, low TCO, and accessibility to all users through some of the most widely used business intelligence tools in the industry such as Microsoft Excel.

Enterprise solution from microsoft Big-Data :

  • Integrated relational and non-relational data for a turnkey Big Data analytics appliance
  • Security, manageability, and high availability for Hadoop
  • Seamless querying across relational and non-relational data using simple T-SQL
  • Insight into virtually all data types with familiar tools through native business intelligence
  • Linear scale-out architecture of up to 6 peta bytes of data
  • Up to 100 times the performance and 15 times more data compression than traditional data
  • warehouses with In-Memory Column store
  • Removal of traditional data warehouse bottlenecks with the MPP capabilities of SQL Server PDW
  • Scalable user accessibility via running of mixed workloads at high concurrency
  • Lowest price per terabyte for a data warehouse appliance in the industry
  • Choice of hardware through HP, Dell, and Quanta

big-data
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APS – microsoft analytics  platform system :

The Analytics Platform System from Microsoft brings Massive Parallel Processing (MPP) data warehouse technology-the SQL Server Parallel Data Warehouse (PDW) together with HDInsight and Microsoft Apache Hadoop. Microsoft offers distinguish technology PolyBase to integrate data from SQL Server PDW and Apache Hadoop simultaneously.

microsoft-aps
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HDInsight

Microsoft’s HDInsight is a Hadoop-based service, built on the Hortonworks Data Platform (HDP) that provides 100% Apache Hadoop infrastructure. HDInsight enables customers to use Structured and Unstructured data in any size.

HDInsight is available in Windows Azure environment and APS (Analytics Platform System). HDInsight makes Apache Hadoop, a MapReduce software framework, available in a simpler, more scalable, and more cost-efficient.

hd-insight
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PDW and poly base - SQL server parallel
Data warehouse (PDW) database :

Microsoft SQL Server Parallel Data warehouse (SQL Server PDW/PDW) is a pre-built Data warehouse appliance which includes Microsoft SQL Server database, third-party server hardware and networking components.

Parallel Data Warehouse is built on a massively parallel processing (MPP) architecture. PDW enables 100% Big-Data infrastructure for the customers. The main competing features of Parallel Data Warehouse is that, it is easy to setup when compare to buying hardware and software and configuring them.

Hadoop data can be stored as relational data in PDW, and query results can be stored back to Hadoop. PDW is empowered to run queries on Hadoop data, now it is possible to do more in-depth data mining, reporting, and analyzing data without MapReducer skills. Now, organizations doesn’t need to look for new skilled resources or train internal resources to multiple new technologies and spend extra cost.

Parallel data warehouse architecture:

pdw-architec
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Poly Base is Mircosoft’s unique technology in PDW for analyzing Hadoop data. Using Poly Base, enterprise can query both Hadoop and PDW data, these queries runs faster and fetch results lot quicker in PDW.

Poly Base, seamlessly select from both Hadoop data and PDW data in the same query, and join data from both data sources.

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