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

Get hands-on with deploying and managing your database services to provide scalable and high-speed data access on CockroachDB Key FeaturesGain insights into CockroachDB and build highly reliable cloud-native applicationsExplore the power of a scalable and highly available cloud-native SQL database to distribute data and workloads automaticallyBuild high-speed database services using CockroachDB and troubleshoot performance issuesBook Description Getting Started with CockroachDB will introduce you to the inner workings of CockroachDB and help you to understand how it provides faster access to distributed data through a SQL interface. The book will also uncover how you can use the database to provide solutions where the data is highly available. Starting with CockroachDB's installation, setup, and configuration, this SQL book will familiarize you with the database architecture and database design principles. You'll then discover several options that CockroachDB provides to store multiple copies of your data to ensure fast data access. The book covers the internals of CockroachDB, how to deploy and manage it on the cloud, performance tuning to get the best out of CockroachDB, and how to scale data across continents and serve it locally. In addition to this, you'll get to grips with fault tolerance and auto-rebalancing, how indexes work, and the CockroachDB Admin UI. The book will guide you in building scalable cloud services on top of CockroachDB, covering administrative and security aspects and tips for troubleshooting, performance enhancements, and a brief guideline on migrating from traditional databases. By the end of this book, you'll have gained sufficient knowledge to manage your data on CockroachDB and interact with it from your application layer. What you will learnBecome well-versed with the overall architecture and design concepts of CockroachDBUnderstand how auto-rebalancing of data can avoid performance bottlenecksGet to know how CockroachDB achieves atomicity, consistency, isolation, and durabilityPartition your data across multiple geolocations to ensure very low latency when serving dataFind out how indexes are stored and the optimizations used to serve query results fasterDiscover the key concepts of deploying and managing CockroachDB clustersWho this book is for Software engineers, database developers, database administrators, and anyone who wishes to learn about the features of CockroachDB and how to build database solutions that are fast, highly available, and cater to business-critical applications, will find this book useful. Although no prior exposure to CockroachDB is required, familiarity with database concepts will help you to get the most out of this book.

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

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

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.

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

Explore the theory and practice of designing and writing serverless applications using examples from the Knative project. With this practical guide, mid-level to senior application developers and team managers will learn when and why to target serverless platforms when developing microservices or applications. Along the way, you'll also discover warning signs that suggest cases when serverless might cause you more trouble than joy. Drawing on author Evan Anderson's 15 years of experience developing and maintaining applications in the cloud, and more than 6 years of experience with serverless platforms at scale, this book acts as your guide into the high-velocity world of serverless application development. You'll come to appreciate why Knative is the most widely adopted open source serverless platform available. With this book, you will: Learn what serverless is, how it works, and why teams are adopting it Understand the benefits of Knative for cloud native development teams Learn how to build a serverless application on Knative Explore the challenges serverless introduces for debugging and the tools that can help improve it Learn why event-driven architecture and serverless compute are complementary but distinct Understand when a serverless approach might not be the right system design