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Database Design and Modeling with PostgreSQL and MySQL

You're reading from   Database Design and Modeling with PostgreSQL and MySQL Build efficient and scalable databases for modern applications using open source databases

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781803233475
Length 222 pages
Edition 1st Edition
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Authors (2):
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Alkin Tezuysal Alkin Tezuysal
Author Profile Icon Alkin Tezuysal
Alkin Tezuysal
Ibrar Ahmed Ibrar Ahmed
Author Profile Icon Ibrar Ahmed
Ibrar Ahmed
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Introduction to Databases
2. Chapter 1: SQL and NoSQL Databases: Characteristics, Design, and Trade-Offs FREE CHAPTER 3. Chapter 2: Building a Strong Foundation for Database Design 4. Part 2: Practical Implementation
5. Chapter 3: Getting Your Hands Dirty with PostgreSQL and MySQL 6. Part 3: Core Concepts in Database Design
7. Chapter 4: Mastering the Building Blocks of Database Design and Modeling 8. Part 4: Advanced Database Techniques
9. Chapter 5: Advanced Techniques for Advanced Databases 10. Chapter 6: Understanding Database Scalability 11. Part 5: Best Practices and Future Trends
12. Chapter 7: Best Practices for Building and Maintaining Your Database 13. Chapter 8: The Future of Databases and Their Designs 14. Index 15. Other Books You May Enjoy

Managing transaction management and concurrency control in NoSQL

Transaction management and concurrency control are critical aspects of database systems that ensure data integrity and consistency in multi-user environments. Traditional SQL databases offer ACID transactions, providing strong consistency guarantees. However, NoSQL databases, which are designed for distributed and scalable environments, often adopt a different approach to transaction management, embracing the BASE model.

Let’s explore the differences between ACID and BASE transactions, the reasons behind NoSQL’s design choices, and the implications for data integrity and concurrency control.

BASE transactions in NoSQL databases

In contrast to ACID, NoSQL databases follow the BASE model for transactions, which relaxes some of the strong consistency guarantees in favor of improved availability and scalability:

  • Basically available: The BASE model prioritizes high availability, ensuring that the system remains accessible and responsive even under adverse conditions. This means that in the presence of network partitions or node failures, the system will continue to respond to user requests.
  • Soft state: NoSQL databases may exhibit temporary inconsistency, referred to as “soft state.” In distributed environments, it is challenging to maintain real-time consistency across all nodes. As a result, some replicas may temporarily diverge, leading to soft state conditions.
  • Eventually consistent: The eventual consistency model in NoSQL databases means that given a sufficiently long period with no further updates, all replicas will eventually converge to a consistent state. The system might temporarily have inconsistent replicas, but these inconsistencies will eventually be resolved.

Reasons for the BASE model in NoSQL databases

In response to the evolving demands of modern distributed and scalable architectures, where traditional database models may fall short, NoSQL databases strategically embrace the BASE model, offering a different paradigm for data consistency and availability:

  • High availability: In modern distributed systems, maintaining high availability is crucial to ensure uninterrupted service, even during network partitions or hardware failures. The BASE model’s focus on availability allows NoSQL databases to remain operational and responsive under adverse conditions.
  • Scalability: NoSQL databases are designed to scale horizontally, distributing data across multiple nodes to handle massive amounts of data and user traffic. Strong consistency in large-scale distributed systems can introduce performance bottlenecks, making the BASE model a more practical choice for scalability.
  • Flexible data models: NoSQL databases accommodate various data models, such as key-value, document, column-family, and graph databases. These diverse data models often require different consistency requirements, making the BASE model more adaptable to the specific needs of each data model.

Implications for data integrity and concurrency control

The adoption of the BASE model in NoSQL databases has implications for data integrity and concurrency control:

  • Eventual consistency: With eventual consistency, applications interacting with NoSQL databases must handle scenarios where data replicas might be temporarily inconsistent. Developers must design their applications to cope with this temporary inconsistency and resolve any conflicts that may arise.
  • Optimistic concurrency control: NoSQL databases often employ optimistic concurrency control mechanisms to handle concurrent read and write operations. This approach allows multiple transactions to proceed concurrently, and conflicts are resolved during the commit phase, reducing the contention for locks.
  • Conflict resolution: In BASE transactions, conflict resolution is a crucial aspect of maintaining data consistency. NoSQL databases use techniques such as last-write-wins or vector clocks to reconcile conflicting updates from different replicas.

Moving from the considerations of data integrity and concurrency control, let’s go into the broader landscape by exploring the advantages and disadvantages of NoSQL Databases

You have been reading a chapter from
Database Design and Modeling with PostgreSQL and MySQL
Published in: Jul 2024
Publisher: Packt
ISBN-13: 9781803233475
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