CockroachDB: The Definitive Guide


Book Description

Get the lowdown on CockroachDB, the elastic SQL database built to handle the demands of today's data-driven world. With this practical guide, software developers, architects, and DevOps teams will discover the advantages of building on a distributed SQL database. You'll learn how to create applications that scale elastically and provide seamless delivery for end users while remaining exceptionally resilient and indestructible. Written from scratch for the cloud and architected to scale elastically to handle the demands of cloud native and open source, CockroachDB makes it easier to build and scale modern applications. If you're familiar with distributed systems, you'll quickly discover the benefits of strong data correctness and consistency guarantees as well as optimizations for delivering ultralow latencies to globally distributed end users. With this thorough guide, you'll learn how to: Plan and build applications for distributed infrastructure, including data modeling and schema design Migrate data into CockroachDB Read and write data and run ACID transactions across distributed infrastructure Optimize queries for performance across geographically distributed replicas Plan a CockroachDB deployment for resiliency across single-region and multiregion clusters Secure, monitor, and optimize your CockroachDB deployment




Database Management using AI: A Comprehensive Guide


Book Description

Database Management Using AI: A Comprehensive Guide is a professional yet accessible exploration of how artificial intelligence (AI) is reshaping the world of database management. Designed for database administrators, data scientists, and tech enthusiasts, this book walks readers through the transformative impact of AI on modern data systems. The guide begins with the fundamentals of database management, covering key concepts such as data models, SQL, and the principles of database design. From there, it delves into the powerful role AI plays in optimizing database performance, enhancing security, and automating complex tasks like data retrieval, query optimization, and schema design. The book doesn't stop at theory. It brings AI to life with practical case studies showing how AI-driven database systems are being used in industries such as e-commerce, healthcare, finance, and logistics. These real-world examples demonstrate AI's role in improving efficiency, reducing errors, and driving intelligent decision-making. Key topics covered include: Introduction to Database Systems: Fundamentals of database management, from relational databases to modern NoSQL systems. AI Integration: How AI enhances database performance, automates routine tasks, and strengthens security. Real-World Applications: Case studies from diverse sectors like healthcare, finance, and retail, showcasing the practical impact of AI in database management. Predictive Analytics and Data Mining: How AI tools leverage data to make accurate predictions and uncover trends. Future Trends: Explore cutting-edge innovations like autonomous databases and cloud-based AI solutions that are shaping the future of data management. With its clear explanations and actionable insights, Database Management Using AI equips readers with the knowledge to navigate the fast-evolving landscape of AI-powered databases, making it a must-have resource for those looking to stay ahead in the digital age.




Cassandra: The Definitive Guide


Book Description

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This expanded second edition—updated for Cassandra 3.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s non-relational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra on site, in the Cloud, or with Docker Integrate Cassandra with Spark, Hadoop, Elasticsearch, Solr, and Lucene




Cassandra: The Definitive Guide


Book Description

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data




The Comprehensive Guide to Databases


Book Description

The Comprehensive Guide to Databases offers an in-depth exploration into the dynamic world of database technology. This guide is designed for a wide audience, from beginners to seasoned professionals, aiming to enhance their understanding of database management. It covers the foundations of database technology, including relational databases, NoSQL solutions, and advanced topics such as distributed systems, big data analytics, and the role of AI and machine learning in database management. With detailed explanations of key concepts, practical applications, and real-world case studies, this book provides readers with the skills necessary to design, implement, and manage database systems effectively. The guide also looks toward the future of database technology, examining emerging trends like cloud databases, data security, and regulatory compliance, making it an essential resource for anyone looking to master the art of database management in the modern digital landscape.




Delta Lake: The Definitive Guide


Book Description

Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu (with contributions from Delta Lake maintainer R. Tyler Croy) share expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data. You'll also uncover how ACID transactions bring reliability to data lakehouses at scale. This book helps you: Understand key data reliability challenges and how Delta Lake solves them Explain the critical role of Delta transaction logs as a single source of truth Learn the Delta Lake ecosystem with technologies like Apache Flink, Kafka, and Trino Architect data lakehouses with the medallion architecture Optimize Delta Lake performance with features like deletion vectors and liquid clustering




Cassandra: The Definitive Guide, (Revised) Third Edition


Book Description

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This revised third edition--updated for Cassandra 4.0 and new developments in the Cassandra ecosystem, including deployments in Kubernetes with K8ssandra--provides technical details and practical examples to help you put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. Developers, DBAs, and application architects looking to solve a database scaling issue or future-proof an application will learn how to harness Cassandra's speed and flexibility. Understand Cassandra's distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh (the CQL shell) Create a working data model and compare it with an equivalent relational model Design and develop applications using client drivers Explore cluster topology and learn how nodes exchange data Maintain a high level of performance in your cluster Deploy Cassandra onsite, in the cloud, or with Docker and Kubernetes Integrate Cassandra with Spark, Kafka, Elasticsearch, Solr, and Lucene




A Definitive Guide to Apache ShardingSphere


Book Description

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 • Understand the core concepts and efficiently set up Apache ShardingSphere • Enhance existing databases with sharding, elastic scaling, encryption, governance features, and more • Import and customize the ecosystem's core features for various application scenarios 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 • Assemble a custom solution using the software's pluggable architecture • Discover how to use Database Plus features effectively • Understand the difference between ShardingSphere-JDBC and ShardingSphere-Proxy • Get to grips with ShardingSphere’s pluggability mechanism • Explore mainstream test models for databases and distributed databases • Perform migrations from an on-premise database to a cloud-based database • Reconfigure your data infrastructure and eliminate switching costs 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.




System Design Interview - An Insider's Guide


Book Description

The system design interview is considered to be the most complex and most difficult technical job interview by many. Those questions are intimidating, but don't worry. It's just that nobody has taken the time to prepare you systematically. We take the time. We go slow. We draw lots of diagrams and use lots of examples. You'll learn step-by-step, one question at a time.Don't miss out.What's inside?- An insider's take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 16 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.




Kubernetes Patterns


Book Description

The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures use new primitives that require a different set of practices than most developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huß from Red Hat provide common reusable elements, patterns, principles, and practices for designing and implementing cloud-native applications on Kubernetes. Each pattern includes a description of the problem and a proposed solution with Kubernetes specifics. Many patterns are also backed by concrete code examples. This book is ideal for developers already familiar with basic Kubernetes concepts who want to learn common cloud native patterns. You’ll learn about the following pattern categories: Foundational patterns cover the core principles and practices for building container-based cloud-native applications. Behavioral patterns explore finer-grained concepts for managing various types of container and platform interactions. Structural patterns help you organize containers within a pod, the atom of the Kubernetes platform. Configuration patterns provide insight into how application configurations can be handled in Kubernetes. Advanced patterns covers more advanced topics such as extending the platform with operators.