Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, (Paperback)
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Navigate the maze of data system design with essential insights into scalability, reliability, and maintainability.
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- Data is at the center of many challenges in system design today. Difficult issues such as scalability, consistency, reliability, efficiency, and maintainability need to be resolved. In addition, there's an overwhelming variety of systems, including relational databases, NoSQL datastores, data warehouses, and data lakes. There are cloud services, on-premises services, and embedded databases. What are the right choices for your application? How do you make sense of all these buzzwords? In this second edition, authors Martin Kleppmann and Chris Riccomini build on the foundation laid in the acclaimed first edition, integrating new technologies and emerging trends. You'll be guided through the maze of decisions and trade-offs involved in building a modern data system, learn how to choose the right tools for your needs, and understand the fundamentals of distributed systems. Peer under the hood of the systems you already use, and learn to use them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Learn how major cloud services are designed for scalability, fault tolerance, and consistency Understand the core principles upon which modern databases are built
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | February, 2026 |
| Pages | 670 |
| Subgenre | Business & Productivity Software |
| Series title | No Series |
| Edition | 2nd Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.00 x 1.35 x 9.19 in (17.8 x 3.4 x 23.3 cm) |
| Assembled product weight | 2.32 lb (1.05 kg) |
| Bisac subject heading | Computers |
Who Should Buy?
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Software Engineers
Engineers looking to understand data architectures and improve their systems' reliability and scalability will greatly benefit.
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Technical Leads
Leads who oversee software projects can enhance team strategies using insights into data management and application design.
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Data Scientists
Professionals wanting to understand the underlying data infrastructure will gain valuable insights to improve analysis capabilities.
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Beginner Programmers
New programmers may find the content too advanced without prior knowledge of data systems and application design.
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Martin Kleppmann All Books Editorial Review
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems is a comprehensive non-fiction book published by O'Reilly Media that dives deep into the critical concepts of building robust and scalable applications. This 2nd Edition paperback, consisting of 670 pages, provides insights into the principles of reliability and maintainability in computing and internet systems, making it an essential read for software developers and IT professionals. The publication, available in English, is designed for those looking to enhance their understanding of data-intensive applications and their architecture. Readers admire its thorough approach and clarity, considering it a valuable resource in the field of business and productivity software.
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Pros
- In-depth exploration of data systems
- Clear explanations of complex concepts
- Suitable for both beginners and experts
- Comprehensive guide on reliability
- Engaging real-world examples
Cons
- Might be dense for casual readers
Product Price History
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Features & Benefits
- Master the challenges of modern data system design.
- Gain insights into scalability, consistency, and reliability.
- Explore the strengths and weaknesses of various tools.
- Understand cloud services designed for fault tolerance.
- Learn to make informed decisions for application needs.
- Unlock the core principles of modern database architecture.
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