Practical Azure SQL Database for Modern Developers: Building Applications in the Microsoft Cloud - Paperback >
/ Practical Azure SQL Database for Modern Developers: Building Applications in the Microsoft Cloud - Paperback

Practical Azure SQL Database for Modern Developers: Building Applications in the Microsoft Cloud - Paperback

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by Davide Mauri (Author), Silvano Coriani (Author), Anna Hoffman (Author)

Here is the expert-level, insider guidance you need on using Azure SQL Database as your back-end data store. This book highlights best practices in everything ranging from full-stack projects to mobile applications to critical, back-end APIs. The book provides instruction on accessing your data from any language and platform. And you learn how to push processing-intensive work into the database engine to be near the data and avoid undue networking traffic. Azure SQL is explained from a developer's point of view, helping you master its feature set and create applications that perform well and delight users.

Core to the book is showing you how Azure SQL Database provides relational and post-relational support so that any workload can be managed with easy accessibility from any platform and any language. You will learn about features ranging from lock-free tables to columnstore indexes, and about support for data formats ranging from JSON and key-values to the nodes and edges in the graph database paradigm. Reading this book prepares you to deal with almost all data management challenges, allowing you to create lean and specialized solutions having the elasticity and scalability that are needed in the modern world.

What You Will Learn
  • Master Azure SQL Database in your development projects from design to the CI/CD pipeline
  • Access your data from any programming language and platform
  • Combine key-value, JSON, and relational data in the same database
  • Push data-intensive compute work into the database for improved efficiency
  • Delight your customers by detecting and improving poorly performing queries
  • Enhance performance through features such as columnstore indexes and lock-free tables
  • Build confidence in your mastery of Azure SQL Database's feature set

Who This Book Is For
Developers of applications and APIs that benefit from cloud database support, developers who wish to master their tools (including Azure SQL Database, and those who want their applications to be known for speedy performance and the elegance of their code

Back Jacket

Here is the expert-level, insider guidance you need on using Azure SQL Database as your back-end data store. This book highlights best practices in everything ranging from full-stack projects to mobile applications to critical, back-end APIs. The book provides instruction on accessing your data from any language and platform. And you learn how to push processing-intensive work into the database engine to be near the data and avoid undue networking traffic. Azure SQL is explained from a developer's point of view, helping you master its feature set and create applications that perform well and delight users.
Core to the book is showing you how Azure SQL Database provides relational and post-relational support so that any workload can be managed with easy accessibility from any platform and any language. You will learn about features ranging from lock-free tables to columnstore indexes, and about support for data formats ranging from JSON and key-values to the nodes and edges in the graph database paradigm. Reading this book prepares you to deal with almost all data management challenges, allowing you to create lean and specialized solutions having the elasticity and scalability that are needed in the modern world.
You will:

  • Master Azure SQL Database in your development projects from design to the CI/CD pipeline
  • Access your data from any programming language and platform
  • Combine key-value, JSON, and relational data in the same database
  • Push data-intensive compute work into the database for improved efficiency
  • Delight your customers by detecting and improving poorly performing queries
  • Enhance performance through features such as columnstore indexes and lock-free tables
  • Build confidence in your mastery of Azure SQL Database's feature set

Author Biography

Davide Mauri is Program Manager in the Azure SQL Database product group. He has been working in the IT field since 1997 and was awarded Data Platform MVP status for 12 consecutive years. He started his career as a full-stack and back-end developer, then focused on databases and data science for 15 years while still keeping alive his passion for development (mainly in C# and Python). He then moved to the Internet of Things (IoT) and big data space where ingesting, processing, and analyzing millions of data points in near real time was his everyday challenge. Building from that experience, he joined Microsoft to help companies worldwide to leverage stream processing at scale. He now works for Azure SQL Database as the developer's voice inside the product group, working to make sure that Azure SQL Database is, and will be, the best database option for developers.

Silvano Coriani has worked on SQL and other data technologies more than 25 years. He started as an embedded systems developer in industrial automation and moved to data acquisition, processing, and analysis in distributed solutions. He has worked on several RDBMS engines (SQL Server 6.0 and later releases, Oracle, IBM DB2, and more recently PostgreSQL), and on NoSQL and other analytical engines such as Spark and Hadoop. He also has experience in C/C++, Visual Basic, Java, and .NET. He has worked in several industries, including manufacturing, retail, and financial services. Since joining Microsoft in 2003, he has been busy helping ISVs and enterprise customers to learn and adopt Microsoft technologies. His experience includes being Developer Evangelist, Software Engineer in the SQL Customer Advisory Team, and most recently working in SQL Customer Success Engineering for the Azure Data team. He is also an active speaker at industry conferences such as PASS Summit and Microsoft Ignite.

Anna Hoffman is Data & Applied Scientist on the Azure Data team at Microsoft. She has worked in Microsoft Research, AI Engineering, and Microsoft Services in her time at Microsoft. She spent several years working on .NET, Python, R, and Java, to democratize AI via tools and services such as Azure Cognitive Services, Azure Machine Learning, and SQL Server (Machine Learning Services and Big Data Clusters). She now spends most of her time working on the Azure SQL Database product team and participating in the community. She has an undergraduate engineering degree from Georgia Institute of Technology, and she is wrapping up a Master of Science in analytics, also at Georgia Institute of Technology (he is always learning). You can follow her on Twitter at @AnalyticAnna.

Sanjay Mishra is Product Leader in Microsoft Azure Data. He leads product management for the Azure SQL Database team, which includes products such as Azure SQL DB, SQL Hyperscale, Elastic Pools. Prior to this role, he served as Technical Advisor to the VP of Azure Data PM, and led the eminent SQLCAT and DataCAT teams.

Jovan Popovic is Senior Program Manager working on Microsoft SQL Server, Azure SQL Database, and Azure Synapse Analytics. He is working in Microsoft Development Center Serbia as Program Manager on several developer-facing SQL Server/Azure SQL features such as T-SQL language enhancements, JSON/temporal support, columnstore/in-memory technologies, and built-in intelligence. He has more than 15 years of experience in various Microsoft technologies with a focus on SQL Server, Azure, ASP.NET, C#, and JavaScript. He has been working in various Microsoft Data Platform teams since 2012. He is a former Microsoft MVP for ASP.NET and has a PhD degree in software engineering from the University of Belgrade. He is am public speaker at top Microsoft conferences, and is author of several books and open-source projects. He enjoys exploring technologies (especially SQL Server capabilities) and finding the best ways to implement the most efficient solutions using them.

Number of Pages: 326
Dimensions: 0.74 x 10 x 7 IN
Illustrated: Yes
Publication Date: November 06, 2020
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