Designing Data-Intensive Applications
BOOK RESOURCE GUIDE

Designing Data-Intensive Applications

Data-systems engineering reference
Authors
Martin Kleppmann
Edition
First Edition
Publisher / year
O’Reilly Media / 2017
ISBN
9781449373320

Opens a third-party website in a new tab.

RESOURCE OVERVIEW

What this resource explores

An exploration of the trade-offs behind reliable, scalable and maintainable data systems. This entry refers to the first edition, published in 2017.

  • Data models and storage systems
  • Replication, partitioning and transactions
  • Batch processing and stream processing

Who it is for

Software developers and technical decision-makers comparing approaches to data-system design.

Background & preparation

Experience building or maintaining applications helps put the system-design trade-offs in context.

A way to approach it

Choose a system question, then compare the relevant storage, replication, transaction and processing chapters rather than treating technologies as interchangeable.

Edition & context

This entry and cover refer to the first edition (2017). Later editions and current implementation details require separate source checks.

CONNECT THE REFERENCES

Related resources & choosing a pathway

FOR YOUR ORGANIZATION

Discuss a related organizational project

Email the project goals, context and scope. Feasibility, implementation conditions and whether to proceed are assessed after receiving the enquiry.

  1. 01

    Describe the need

    Email goals, context and scope from your own email application.

  2. 02

    Clarify by email

    Clarify the question and conditions, adding a summary where needed.

  3. 03

    Assess whether to proceed

    Assess feasibility, implementation and required resources.

  4. 04

    Agree any next steps

    If feasible, discuss scope, timing, cost and arrangements.

MNV LIMITED
[email protected]
+852 2661 2188