MongoDB Atlas is a database as a service from MongoDB, providing all of the features of the database, without the operational heavy lifting required for any new application. This guide describes the best practices to help you get the most out of the MongoDB Atlas service, including: schema design, capacity planning, security, and performance optimization.
A new generation of technologies is needed to consume and exploit today's real time, fast moving data sources. Apache Kafka, originally developed at LinkedIn, has emerged as one of these key new technologies. This paper explores the use-cases and architecture for Kafka, and how it integrates with MongoDB to build sophisticated data-driven applications that exploit new sources of data.
In the last few years, microservices have come to the forefront of the conversation. They have been rapidly adopted, due to their ability to provide modularity, scalability, high availability, as well as facilitate organizational alignment.
This white paper discusses the background behind microservices, their advantages, and how new generations of technologies, such as MongoDB, enable them.
MongoDB 3.2 is a giant leap forward that helps organizations standardize on a single, modern database for their new, mission-critical applications. Download the white paper to learn about the latest features in 3.2.
Hadoop-based data lakes are enabling organizations to efficiently capture unprecedented volumes of data generated by new classes of highly connected applications. But without being able to expose that data to operational applications, users are struggling to maximize returns on their Hadoop investments.
Read this white paper to learn how to create an operational data lake.
Organizations are building their applications around microservice architectures because of the flexibility, speed of delivery, and maintainability they deliver. Containers are the technology powering this adoption.
This white paper introduces the concepts behind containers and orchestration, then explains the available technologies and how to use them with MongoDB.
Apache Spark is one of the fastest growing big data projects in the history of the Apache Software Foundation. With its memory-oriented architecture, flexible processing libraries and ease-of-use, Spark has emerged as a leading distributed computing framework for real-time analytics.
Independent evaluators United Software Associates released new research based on Yahoo! Cloud Serving Benchmark (YCSB) demonstrating that MongoDB overwhelmingly outperforms key value stores. The results show that MongoDB provides greater scalability than NoSQL vendors Cassandra and Couchbase in all tests, by as much as 13x.
This guide provides an overview of MongoDB and its deployment on the AWS cloud platform. It discusses best practices and implementation characteristics such as performance, high availability, and security, and focuses on AWS features relevant to MongoDB that help ensure scalability, continuous uptime, and disaster recovery.
Independent evaluators United Software Associates demonstrate that MongoDB overwhelmingly outperforms key value stores Couchbase and Cassandra. The results show that MongoDB smokes NoSQL vendors in terms of both throughput and latency across a number of configurations.
Can the choice of database really dictate business outcomes? Consider:
* A leading insurance company delivering a new application in just 3 months, after struggling for 8 years with a legacy database.
* A global telecoms operators accelerating time to market by 4x and improving customer experience by 10x.
* A Tier 1 investment bank estimating savings of $40m.
What do they all have in common? They all selected MongoDB to deliver applications never previously possible. Download the white paper to learn more
Organizations spend too much time and money on databases — over $40B per year — and still more on the resources required to manage them. In this paper, tell the stories of large enterprise customers — like MetLife and Telefonica — who have adopted MongoDB and as a result are operating faster, better, leaner. We then provide a playbook for emulating these success stories with actionable steps to become faster, better, leaner too.
Relational databases have a long-standing position in most organizations, and for good reason. But companies are increasingly considering alternatives to legacy relational infrastructure, such as NoSQL databases. As companies evaluate these products, they should consider 5 critical dimensions to make the right choice for their applications and their businesses. In this paper, we describe these dimensions and show why MongoDB is the most widely used NoSQL database in the market.
Despite the hype, big data is more than just a buzzword. Big data is enabling organizations to create new products, to outpace their competitors and to save tens of millions of dollars. In this paper, we begin with a description of big data and the data management landscape. Next, we describe examples of customers innovating with big data using MongoDB, the leading non-relational database, which has been a catalyst of the big data movement. Finally, given the nascent state of the market, we provide guidance to organizations selecting technologies for their big data projects.
In this introductory technical paper, you'll learn:
* The architecture of MongoDB.
* How MongoDB builds and runs applications today.
* MongoDB's document data model, query model, data management, consistency, durability, availability and performance.
This guide outlines best practices and considerations for achieving performance at scale in a MongoDB system in a number of key areas, including:
* Hardware, application patterns, schema design and indexing.
* Disk I/O, Amazon EC2.
* Designing for benchmarks.
This document provides guidance on best practices for deploying and managing MongoDB clusters. It assumes familiarity with the architecture of MongoDB and a basic understanding of concepts related to enterprise software deployment. Because MongoDB is designed to be simple to administer and to deploy, most operations professionals find they can become competent with MongoDB in a short period of time and with minimal training.
The frequency and severity of data breaches continues to escalate year on year, with researchers estimating attacks increasing nearly 50% year on year. Databases store an organization’s most important information assets, so securing them is top of mind for administrators.
Data is the core currency in today’s digital economy. In the same way that central banks take extensive measures to safeguard this vital asset, organizations need to take every practical measure to protect their data. This white paper will walk you through the key considerations when evaluating a backup strategy, and the different methods for protecting your mission critical MongoDB data.
This guide explains how to migrate from a relational database to MongoDB and the relevant technical considerations, such as differences between the relational and document data models and the implications for schema design. The guide also covers indexing, queries, application integration and data migration.
In this white paper, we compare the total cost of ownership (TCO) of MongoDB and Oracle. It can be faster and cheaper to develop and deploy applications on MongoDB than on Oracle Database, yielding both bottom-line benefits – lower developer and administrative costs – and topline advantages – it is easier and faster to evolve applications to meet changing business and market conditions.
Apollo Group was planning a strategic initiative to create a cloud-based learning management platform, and the project team knew that the existing Oracle database had neither the flexibility nor the capacity to meet their future needs. This paper shares the methodologies used to evaluate alternative technologies, and why they ended up selecting MongoDB.
Big data is an essential extension of BI & analytics platforms, presenting new sources of operational insight & discovery. However, the rate of data ingestion coupled with its complexity & volume are beyond the constraints of many traditional databases used in today's BI systems. With its rich document model, powerful analytical capabilities and integration with leading BI and analytics tools, learn how MongoDB provides a foundation to integrate online big data with existing BI and analytics platforms.
As more applications are exposed as services to global audiences, the scalability and availability of your database across geographic regions becomes a critical consideration in systems selection and design.
In this white paper you will learn about:
* MongoDB’s cross-region data center awareness
* Deployment topologies, including active/active data centers and disaster recovery
* How organizations in diverse industries use MongoDB to scale global operations
As more internal business units and project teams build modern applications on MongoDB, architects and operations teams can improve agility, efficiency, accountability and governance by offering MongoDB-as-a-Service.
This white paper provides the top 10 considerations you make including:
* Systems design
* Virtualization and multi-tenancy
* Management, accounting and compliance
MongoDB and Bosch Software Innovations have collaborated to build a powerful Internet of Things application platform to support new IoT business models.
In this white paper you will learn:
- New use-cases enabled by the IoT
- Solutions to manage devices, assets and events in an IoT platform
- How to overcome the 5 key data management challenges presented by the IoT
Adobe Experience Manager (AEM) 6.1 is a major step forward in enabling marketing teams to create, manage, and optimize digital customer experiences across channels. As a persistence layer for AEM, MongoDB introduces several new capabilities which we will explore in this white paper.
As one of the leading M2M, IoT and Big Data research and consulting firms, Machina Research has unique insight into how big data presents challenges and opportunities in the rapidly evolving IoT landscape. Download their research note to learn:
- Key database requirements to address IoT applications
- Impacts to traditional data management technologies
- Alternative technologies that should be on your radar
Telcos are under attack from software companies and over-the-top competitors. MongoDB enables telcos to couple the resources of a multinational with the speed of a startup, helping them to expand their customer bases, increase ARPU and reduce churn.
The consumer TV experience has changed. Gone are the days of the static, single-threaded viewing experience in the living room. Today, consumers have new requirements; they want content on-demand, on their device of choice and on their terms. Given the rise of competitive services from companies like Netflix and pressure on existing revenue streams, service providers (telcos, cable and satellite providers) need to evolve their offerings. The good news is, they may not need a new business model so much as a new database.
Subscriber Data Management (SDM) is core to the future of telcos, battling to prevent relegation to the status of a dumb pipe. In this white paper, you'll learn:
* The promise and challenges of SDM, including the rise of big data.
* Why MongoDB for SDM, with samples of subscriber data schema.
* SDM in Action with MongoDB - How Telefonica liberated its subscriber data.
* Resources to get started today.
As companies move more and more towards decoupling architectures, it is increasingly important that enterprises maintain tight feedback loops and build software that can be released into production at any time.
Today’s digitally-oriented society has created a new generation of shopper – one who lives across channels and expects personalization, perfect information, and instant gratification. These evolving consumer behaviors and expectations can be an incredible challenge for retailers, but they also represent a tremendous opportunity for leading brands to further differentiate themselves from the competition with technologies and processes that enable the omni-channel retail experience.
MongoDB 3.0 is the newest and most significant release of the world’s fastest growing database. MongoDB 3.0 radically expands the use cases for MongoDB, allowing you to use it for the vast majority of all new applications. By improving performance by 7x - 10x, reducing storage needs by up to 80%, and lowering operations overhead by up to 95%, MongoDB 3.0 also dramatically improves your ability to deliver apps to market faster and more efficiently than ever before.
MongoDB 2.6 builds on five years of innovation and hundreds of thousands of deployments to provide a new foundation for the database, drivers and sophisticated management tools that make operating MongoDB simple at any scale.