A MongoDB White Paper

Performance Best Practices for
MongoDB
MongoDB 3.2
December 2015

Table of Contents
Introduction

1

Pluggable Storage Engines

1

Hardware

2

Application Patterns

4

Schema Design & Indexes

5

Disk I/O

6

Considerations for Amazon EC2

7

Considerations for Benchmarks

7

We Can Help

9

Resources

9

Introduction
MongoDB is a high-performance, scalable database designed for a broad array of modern applications. It is used by organizations of all sizes to power on-line, operational applications where low latency, high throughput and continuous availability are critical requirements of the system. For a discussion on the architecture of MongoDB and some of its underlying assumptions, see the MongoDB
Architecture Guide. For a discussion on operating a
MongoDB system, see the MongoDB Operations Best
Practices.

This guide outlines considerations for achieving performance at scale in a MongoDB system across a number of key dimensions, including hardware, application

MongoDB Pluggable Storage
Engines

patterns, schema design and indexing, disk I/O, Amazon
EC2, and designing for benchmarks. While this guide is broad in scope, it is not exhaustive. Following the recommendations in this guide will reduce the likelihood of encountering common performance limitations, but it does not guarantee good performance in your application.

MongoDB 3.0 exposed a new storage engine API, enabling the integration of pluggable storage engines that extend MongoDB with new capabilities, and enable optimal use of specific hardware architectures. MongoDB 3.2 ships with multiple supported storage engines:

MongoDB works closely with users to help them optimize their systems. Users should monitor their systems to identify bottlenecks and limitations. There are a variety of
tools