Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems


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Data is on the heart of many challenges in system design at present. Difficult points have to be discovered, reminiscent of scalability, consistency, reliability, effectivity, and maintainability. In addition, we’ve an amazing number of instruments, together with relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the best decisions on your software? How do you make sense of all these buzzwords?

In this sensible and complete information, writer Martin Kleppmann helps you navigate this numerous panorama by inspecting the professionals and cons of varied applied sciences for processing and storing knowledge. Software retains altering, however the basic rules stay the identical. With this ebook, software program engineers and architects will learn to apply these concepts in apply, and learn how to make full use of knowledge in fashionable purposes.

  • Peer underneath the hood of the programs you already use, and learn to use and function them extra successfully
  • Make knowledgeable choices by figuring out the strengths and weaknesses of various instruments
  • Navigate the trade-offs round consistency, scalability, fault tolerance, and complexity
  • Understand the distributed programs analysis upon which fashionable databases are constructed
  • Peek behind the scenes of main on-line providers, and be taught from their architectures


From the Publisher

Designing Data-Intensive ApplicationsDesigning Data-Intensive Applications

Who Should Read This Book?

If you develop purposes which have some type of server/backend for storing or processing knowledge, and your purposes use the web (e.g., net purposes, cellular apps, or internet-connected sensors), then this ebook is for you.

This ebook is for software program engineers, software program architects, and technical managers who like to code. It is particularly related if you’ll want to make choices concerning the structure of the programs you’re employed on—for instance, if you’ll want to select instruments for fixing a given downside and determine how greatest to use them. But even when you have no selection over your instruments, this ebook will assist you higher perceive their strengths and weaknesses.

You ought to have some expertise constructing web-based purposes or community providers, and you need to be acquainted with relational databases and SQL. Any non-relational databases and different data-related instruments you already know are a bonus, however not required. A common understanding of frequent community protocols like TCP and HTTP is useful. Your selection of programming language or framework makes no distinction for this ebook.

If any of the next are true for you, you’ll discover this ebook priceless:

You need to learn to make knowledge programs scalable, for instance, to assist net or cellular apps with hundreds of thousands of customers.

You must make purposes extremely out there (minimizing downtime) and operationally sturdy.

You are in search of methods of creating programs simpler to take care of in the long term, at the same time as they develop and as necessities and applied sciences change.

You have a pure curiosity for the best way issues work and need to know what goes on inside main web sites and on-line providers. This ebook breaks down the internals of varied databases and knowledge processing programs, and it’s nice enjoyable to discover the brilliant pondering that went into their design.

Designing Data-Intensive ApplicationsDesigning Data-Intensive Applications

Sometimes, when discussing scalable knowledge programs, individuals make feedback alongside the traces of, ‘You’re not Google or Amazon. Stop worrying about scale and simply use a relational database’. There is fact in that assertion: constructing for scale that you simply don’t want is wasted effort and might lock you into an rigid design. In impact, it’s a type of untimely optimization. However, it’s additionally vital to decide on the best device for the job, and completely different applied sciences every have their very own strengths and weaknesses. As we will see, relational databases are vital however not the ultimate phrase on coping with knowledge.

Scope of This Book

This ebook doesn’t try to present detailed directions on learn how to set up or use particular software program packages or APIs, since there may be already loads of documentation for these issues. Instead we talk about the varied rules and trade-offs which might be basic to knowledge programs, and we discover the completely different design choices taken by completely different merchandise.

We look primarily on the structure of knowledge programs and the methods they’re built-in into data-intensive purposes. This ebook doesn’t have area to cowl deployment, operations, safety, administration, and different areas—these are advanced and vital subjects, and we wouldn’t do them justice by making them superficial facet notes on this ebook. They deserve books of their very own.

Many of the applied sciences described on this ebook fall throughout the realm of the Big Data buzzword. However, the time period ‘Big Data’ is so overused and underdefined that it’s not helpful in a critical engineering dialogue. This ebook makes use of much less ambiguous phrases, reminiscent of single-node versus distributed programs, or on-line/interactive versus offline/batch processing programs.

This ebook has a bias towards free and open supply software program (FOSS), as a result of studying, modifying, and executing supply code is an effective way to know how one thing works intimately. Open platforms additionally scale back the chance of vendor lock-in. However, the place applicable, we additionally talk about proprietary software program (closed-source software program, software program as a service, or firms’ in-house software program that’s solely described in literature however not launched publicly).

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