Stretch DB allows the moving of historical or less frequently needed data dynamically and transparently to Microsoft Azure. Data is always available and online, and you don't need to change queries in your solutions; SQL Server takes care of the location of data and combines retrieving data from the local server and remote Azure location. Therefore, you can completely delegate your cold data to Azure and reduce storage, maintenance, and implementation costs of an on-premises solution for cold data storage and availability. However, there are many limitations to using Stretch DB and most OLTP tables cannot be stretched to the cloud—at least not without schema and constraint changes. Stretch Database brings maximum benefits to tables with historical data that is rarely used. You can calculate the price for data storage and querying against the Azure database and...
Mastering SQL Server 2017
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Mastering SQL Server 2017
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Overview of this book
Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation.
You’ll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you’ll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks.
By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence.
This Learning Path includes content from the following Packt books:
SQL Server 2017 Developer's Guide by Miloš Radivojevi?, Dejan Sarka, et. al
SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al
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Mastering SQL Server 2017
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Table of Contents (20 chapters)
Title Page
Copyright
About Packt
Preface
SQL Server Tools
JSON Support in SQL Server
Stretch Database
Temporal Tables
Columnstore Indexes
SSIS Setup
What Is New in SSIS 2016
Key Components of a Modern ETL Solution
Dealing with Data Quality
Unleash the Power of SSIS Script Task and Component
On-Premises and Azure Big Data Integration
Extending SSIS Custom Tasks and Transformations
Scale Out with SSIS 2017
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