Data warehousing and big data

Data warehouse solutions, from terabytes to petabytes

Data warehouse solutions, from terabytes to petabytes

To fully realise the value of data, you need a complete platform that can manage both structured and unstructured data with security, consistency and credibility. Data warehouse and big data solutions from Microsoft provide a trusted infrastructure that can handle all types of data, and scale from terabytes to petabytes, with real-time performance.


You need a new kind of data warehouse to handle the exponentially growing volume of data, the variety of semi-structured and unstructured data types, and the velocity of real-time data processing. The Microsoft modern data warehouse solution integrates your traditional data warehouse with unstructured big data—and it can handle data of all sizes and types, with real-time performance.

There are massive volumes of information out there just waiting to be turned into actionable insights, and you need a powerful platform to make sense of it. With SQL Server in-memory columnstore, you’ll get up to 100x faster query performance. And with the Polybase capabilities in Microsoft’s Analytics Platform System (APS), and in SQL Server 2016, you’ll have the ability to query across relational and non-relational sources like Hadoop.


  • Provide a trusted infrastructure that gives users confidence in the credibility and consistency of the data
  • Incorporate a wider variety of data sources that include mobile, social, scanners, photos, videos, sensors, devices, RFID, web logs, advanced analytics, click streams, machine learning, and third-party data sources
  • Query both traditional relational data and these new data types with common T-SQL commands using Polybase
  • Scale from tens of terabytes up to multiple petabytes by incrementally adding nodes to your existing infrastructure
  • Change tracking to identify configuration changes in your environment that can help pinpoint operational issues
  • Enable users to get results from their queries in near real-time with streaming technologies. Queries that took hours can be reduced to minutes or seconds through in-memory