PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS effective strategies for distributed cloud-native applications and data-driven modernization
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Santana, O., & Varela, K. (2023). PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS: effective strategies for distributed cloud-native applications and data-driven modernization (1st edition.). Packt Publishing Ltd..
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Santana, Otávio and Karina, Varela. 2023. PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS: Effective Strategies for Distributed Cloud-native Applications and Data-driven Modernization. Birmingham, UK: Packt Publishing Ltd.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Santana, Otávio and Karina, Varela. PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS: Effective Strategies for Distributed Cloud-native Applications and Data-driven Modernization Birmingham, UK: Packt Publishing Ltd, 2023.
Harvard Citation (style guide)Santana, O. and Varela, K. (2023). PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS: effective strategies for distributed cloud-native applications and data-driven modernization. 1st edn. Birmingham, UK: Packt Publishing Ltd.
MLA Citation, 9th Edition (style guide)Santana, Otávio,, and Karina Varela. PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS: Effective Strategies for Distributed Cloud-native Applications and Data-driven Modernization 1st edition., Packt Publishing Ltd., 2023.
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Grouped Work ID | 40e24066-076e-3d2f-d871-d9aabb855ee5-eng |
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Full title | persistence best practices for java applications effective strategies for distributed cloud native applications and data driven modernization |
Author | santana otávio |
Grouping Category | book |
Last Update | 2025-01-24 12:33:29PM |
Last Indexed | 2025-01-29 03:11:48AM |
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First Loaded | Jan 18, 2025 |
Last Used | Jan 23, 2025 |
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100 | 1 | |a Santana, Otávio,|e author. | |
245 | 1 | 0 | |a PERSISTENCE BEST PRACTICES FOR JAVA APPLICATIONS|h [electronic resource] :|b effective strategies for distributed cloud-native applications and data-driven modernization /|c Otávio Santana, Karina Varela. |
250 | |a 1st edition. | ||
260 | |a Birmingham, UK :|b Packt Publishing Ltd.,|c 2023. | ||
300 | |a 1 online resource | ||
505 | 0 | |a Cover -- Title Page -- Copyright and Credit -- Dedicated -- Contributors -- Table of Contents -- Preface -- Part 1: Persistence in Cloud Computing -- Storing and Managing Data in Modern Software Architecture -- Chapter 1: The History of Data Storage -- From the Caves to the Cloud -- Why do databases exist? -- The challenges of handling data -- Characteristics of Java persistence frameworks -- The cloud's effect on stateful solutions -- Exploring the trade-offs of distributed database systems -- a look into the CAP theorem and beyond -- Summary | |
505 | 8 | |a Chapter 2: Exploring the Multiple Database Flavors -- A look back at relational databases -- A deep dive into non-relational databases (NoSQL) -- NoSQL database types -- key-value -- NoSQL database types -- document -- NoSQL database types -- wide-column/column-family -- NoSQL database types -- graph -- NewSQL databases -- trying to get the best out of both worlds -- Summary -- Chapter 3: ChaExploring Architectural Strategies and Cloud Usage -- The cloud's influence on software architecture design -- Design patterns -- the essential building blocks for software architects -- Monolithic architecture | |
505 | 8 | |a Microservices architecture -- Common pitfalls of microservices adoption -- Cloud deployment strategies that favor modern stateful solutions -- Why the hybrid and multi-cloud models matter -- Distributed systems and their impact on data systems -- Example -- architecting a food delivery solution -- The basic scenario -- The challenges of integrating services around a central piece of data -- Summary -- Chapter 4: Design Patterns for Data Management in Cloud-Native Applications -- Technical requirements -- Design patterns applied to the Java persistence layer -- Unstructured code | |
505 | 8 | |a The data mapper pattern -- The DAO pattern -- Repository pattern boosted by DDD -- The active record pattern -- Navigating the Java mapping landscape -- evaluating framework trade-offs -- Data transfer between the view and underlying layers -- Summary -- Part 2: Jakarta EE, MicroProfile, Modern Persistence Technologies, and Their Trade-Offs -- Chapter 5: Jakarta EE and JPA -- State of Affairs -- Technical requirements -- Jakarta EE overview -- Framework unveiled -- reflection versus reflectionless solutions -- JPA state of affairs -- JPA and database mapping patterns | |
505 | 8 | |a The power of JPA with Quarkus and Panache cloud-native runtimes -- Setting up the new service -- Persistent entities and database operations -- Exposing REST endpoints for data manipulation -- Even faster development speed -- automatic endpoint generation -- General JPA-related performance considerations -- Summary -- Chapter 6: NoSQL in Java Demystified -- One API to Rule Them All -- Technical requirements -- Understanding NoSQL database trade-offs -- Consuming NoSQL databases with JNoSQL -- Key-value databases -- Column databases -- Document databases -- Graph databases -- Summary | |
520 | |a The definitive guide for designing and delivering reliable and high-performing persistence layers using Java in the cloud-native age Purchase of the print or Kindle book includes a free PDF eBook Key Features Uncover database patterns for designing readable and maintainable architectures and Java applications Master various techniques to overcome application and architecture persistence challenges Discover painless application modernization with change-data-capture powered by cloud-native technologies Book Description Having a solid software architecture breathes life into tech solutions. In the early stages of an application's development, critical decisions need to be made, such as whether to go for microservices, a monolithic architecture, the event-driven approach, or containerization. In Java contexts, frameworks and runtimes also need to be defi ned. But one aspect is often overlooked - the persistence layer - which plays a vital role similar to that of data stores in modern cloud-native solutions. To optimize applications and data stores, a holistic understanding of best practices, technologies, and existing approaches is crucial. This book presents well-established patterns and standards that can be used in Java solutions, with valuable insights into the pros and cons of trending technologies and frameworks used in cloud-native microservices, alongside good Java coding practices. As you progress, you'll confront the challenges of cloud adoption head-on, particularly those tied to the growing need for cost reduction through stack modernization. Within these pages, you'll discover application modernization strategies and learn how enterprise data integration patterns and event-driven architectures enable smooth modernization processes with low-to-zero impact on the existing legacy stack. What you will learn Gain insights into data integration in Java services and the inner workings of frameworks Apply data design patterns to create a more readable and maintainable design system Understand the impact of design patterns on program performance Explore the role of cloud-native technologies in modern application persistence Optimize database schema designs and leverage indexing strategies for improved performance Implement proven strategies to handle data storage, retrieval, and management efficiently Who this book is for If you're a developer, engineer, or software architect working in the field of software development, particularly with a focus on Java solutions, this book is for you. | ||
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