Become well versed with all of ShardingSphere's features for every data management need with this comprehensive guide put together by ShardingSphere's founder and core contributors
Key Features:
Book Description:
Apache ShardingSphere is a new open source ecosystem for distributed data infrastructures based on pluggability and cloud-native principles that helps enhance your database.
This book begins with a quick overview of the main challenges faced by database management systems (DBMSs) in production environments, followed by a brief introduction to the software's kernel concept. After that, using real-world examples of distributed database solutions, elastic scaling, DistSQL, synthetic monitoring, database gateways, and SQL authority and user authentication, you'll fully understand ShardingSphere's architectural components, how they're configured and can be plugged into your existing infrastructure, and how to manage your data and applications. You'll also explore ShardingSphere-JDBC and ShardingSphere-Proxy, the ecosystem's clients, and how they can work either concurrently or independently to address your needs. You'll then learn how to customize the plugin platform to define personalized user strategies and manage multiple configurations seamlessly. Finally, the book enables you to get up and running with functional and performance tests for all scenarios.
By the end of this book, you'll be able to build and deploy a customized version of ShardingSphere, addressing the key pain points encountered in your data management infrastructure.
What You Will Learn:
Who this book is for:
This book is for database administrators working with distributed database solutions who are looking to explore the capabilities of Apache ShardingSphere. DBAs looking for more capable, flexible, and cost-effective alternatives to the solutions they're currently utilizing will also find this book helpful. To get started with this book, a basic understanding of, or even an interest in, databases, relational databases, SQL languages, cloud computing, and data management in general is needed.
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