High Performance with MongoDB
Best practices for performance tuning, scaling, and architecture
Published on 5. September 2025
Book
Paperback/Softback
410 pages
978-1-83702-263-2 (ISBN)
Description
Practical strategies to help you design, optimize, and operate MongoDB deployments for performance, resilience, and growth
Key Features
Identify and fix performance bottlenecks with practical diagnostic and optimization strategies
Optimize schema design, indexing, storage, and system resources for real-world workloads
Scale confidently with in-depth coverage of replication, sharding, and cluster management techniques
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionWith data as the new competitive edge, performance has become the need of the hour. As applications handle exponentially growing data and user demand for speed and reliability rises, three industry experts distill their decades of experience to offer you guidance on designing, building, and operating databases that deliver fast, scalable, and resilient experiences.
MongoDB's document model and distributed architecture provide powerful tools for modern applications, but unlocking their full potential requires a deep understanding of architecture, operational patterns, and tuning best practices. This MongoDB book takes a hands-on approach to diagnosing common performance issues and applying proven optimization strategies from schema design and indexing to storage engine tuning and resource management.
Whether you're optimizing a single replica set or scaling a sharded cluster, this book provides the tools to maximize deployment performance. Its modular chapters let you explore query optimization, connection management, and monitoring or follow a complete learning path to build a rock-solid performance foundation. With real-world case studies, code examples, and proven best practices, you'll be ready to troubleshoot bottlenecks, scale efficiently, and keep MongoDB running at peak performance in even the most demanding production environments.What you will learn
Diagnose and resolve common performance bottlenecks in deployments
Design schemas and indexes that maximize throughput and efficiency
Tune the WiredTiger storage engine and manage system resources for peak performance
Leverage sharding and replication to scale and ensure uptime
Monitor, debug, and maintain deployments proactively to prevent issues
Improve application responsiveness through client driver configuration
Who this book is forThis book is for developers, database administrators, system architects, and DevOps engineers focused on performance optimization of MongoDB. Whether you're building high-throughput applications, managing deployments in production, or scaling distributed systems, you'll gain actionable insights. Basic knowledge of MongoDB is assumed, with chapters designed progressively to support learners at all levels.
Key Features
Identify and fix performance bottlenecks with practical diagnostic and optimization strategies
Optimize schema design, indexing, storage, and system resources for real-world workloads
Scale confidently with in-depth coverage of replication, sharding, and cluster management techniques
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionWith data as the new competitive edge, performance has become the need of the hour. As applications handle exponentially growing data and user demand for speed and reliability rises, three industry experts distill their decades of experience to offer you guidance on designing, building, and operating databases that deliver fast, scalable, and resilient experiences.
MongoDB's document model and distributed architecture provide powerful tools for modern applications, but unlocking their full potential requires a deep understanding of architecture, operational patterns, and tuning best practices. This MongoDB book takes a hands-on approach to diagnosing common performance issues and applying proven optimization strategies from schema design and indexing to storage engine tuning and resource management.
Whether you're optimizing a single replica set or scaling a sharded cluster, this book provides the tools to maximize deployment performance. Its modular chapters let you explore query optimization, connection management, and monitoring or follow a complete learning path to build a rock-solid performance foundation. With real-world case studies, code examples, and proven best practices, you'll be ready to troubleshoot bottlenecks, scale efficiently, and keep MongoDB running at peak performance in even the most demanding production environments.What you will learn
Diagnose and resolve common performance bottlenecks in deployments
Design schemas and indexes that maximize throughput and efficiency
Tune the WiredTiger storage engine and manage system resources for peak performance
Leverage sharding and replication to scale and ensure uptime
Monitor, debug, and maintain deployments proactively to prevent issues
Improve application responsiveness through client driver configuration
Who this book is forThis book is for developers, database administrators, system architects, and DevOps engineers focused on performance optimization of MongoDB. Whether you're building high-throughput applications, managing deployments in production, or scaling distributed systems, you'll gain actionable insights. Basic knowledge of MongoDB is assumed, with chapters designed progressively to support learners at all levels.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 22 mm
Weight
762 gr
ISBN-13
978-1-83702-263-2 (9781837022632)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Asya Kamsky is a Principal KnowItAll at MongoDB, where she has worked since 2012. Before discovering MongoDB, she spent nearly two decades coaxing relational databases into doing what they were never designed to do at a series of startups, most of which no one remembers. Asya has an extensive background in software development, databases, and telling people what they're doing wrong. Ger Hartnett is a Lead Engineer on MongoDB's product performance team, where he loves working on fascinating optimization and scaling challenges. Before MongoDB, he founded a startup that built a project communication platform (that had scaling issues). Prior to that, he architected and tuned embedded software at Intel, where he co-authored a book. Even before that, he developed systems at companies including Tellabs, Digital, and Motorola. Alex Bevilacqua is the Lead Product Manager at MongoDB for Developer Experience. Prior to joining MongoDB in 2018, he worked as a software engineer and systems architect, implementing solutions in a number of languages, technologies, and frameworks. Aside from his passion for programming that consumes more than just his working hours, Alex can typically be found at an arena with one of his kids, both of whom play rep hockey.
Content
Table of Contents
Systems and MongoDB Architecture
Schema Design for Performance
Indexes
Aggregations
Replication
Sharding
Storage Engines
Change Streams
Transactions
Client Libraries
Managing Connections and Network Performance
Advanced Query and Indexing Concepts
Operating Systems and System Resources
Monitoring and Observability
Debugging Performance Issues
Systems and MongoDB Architecture
Schema Design for Performance
Indexes
Aggregations
Replication
Sharding
Storage Engines
Change Streams
Transactions
Client Libraries
Managing Connections and Network Performance
Advanced Query and Indexing Concepts
Operating Systems and System Resources
Monitoring and Observability
Debugging Performance Issues