Columnar storage brings a completely new set of possibilities to SQL Server. You can get lightning performance in analytical queries right from your data warehouse, without a special analytical database management system. This chapter started by describing features that support analytical queries in SQL Server other than columnar storage. You can use row or page data compression levels, bitmap filtered hash joins, filtered indexes, indexed views, window analytical and aggregate functions, table partitioning, and more. However, columnar storage adds an additional level of compression and performance boost. You learned about the algorithms behind the fantastic compression delivered by columnar storage. This chapter also included a lot of code, showing you how to create and use the nonclustered and the clustered columnstore indexes, including updating the data, creating constraints...
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
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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Customer Reviews