Getting Started with MongoDB Atlas
Learn how to leverage MongoDB Atlas, the modern, multi-cloud data platform, and deploy your first cluster. Plus, learn the foundations of MongoDB and get an overview of its architecture.
Getting Started with MongoDB Atlas
Unit Overview
In this unit, you'll be introduced to everything you need to know to get started with MongoDB Atlas, our multi-cloud data platform. First, you'll learn the foundations of MongoDB and its architecture. We'll explore what it means for MongoDB to be a distributed database and offer a flexible schema in the form of the document model. Then, you'll get an overview of Atlas and its features, which provide a streamlined experience for working with MongoDB. Finally, you'll deploy your first Atlas cluster and explore the Atlas UI.
Lessons in This Unit
- Lesson 1 - Foundations of MongoDB
- Lesson 2 - MongoDB Architecture Overview
- Lesson 3 - Atlas Overview
- Lesson 4 - Deploying an Atlas Cluster
- Lesson 5 - Exploring the Atlas UI
Katie Redmiles | Senior Curriculum Designer
Katie is a Senior Curriculum Designer at MongoDB. Before joining the Curriculum team, Katie worked on the University Enablement team developing Learning Bytes and instructional materials for the MongoDB for Academia program. Katie also worked within the Digital Learning Division at the Foreign Service Institute where she honed her skills at developing online learning for a global audience. Katie is passionate about making education accessible and engaging for everyone.
Camden Kirkland I Senior Technical Instructor
Cam is a Senior Technical Instructor at MongoDB where he delivers courses for a wide variety of foundational and advanced topics on the database. Prior to MongoDB, he was a Curriculum Architect designing technical programs for web development, data analytics, and financial technologies for universities all over the country. In a past life he was a Chemist making sure your transformers didn't catch fire.
Emily Pope | Lead Curriculum Designer
Emily Pope is a Lead Curriculum Designer at MongoDB. She loves learning and loves making it easy for others to learn how and when to use deeply technical products. Recently, she's been creating AI and vector search content for MongoDB University. Before that, she's created learning experiences on databases, computer science, full stack development, and even clinical trial design and analysis. Emily holds an Ed.M. in International Education Policy from Harvard Graduate School of Education and began her career as an English teacher in Turkiye with the Fulbright program.
Manuel Fontan Garcia | Senior Technologist
Manuel is a Senior Technologist on the Curriculum team at MongoDB. Previously he was a Senior Technical Services Engineer in the Core team at MongoDB. In between Manuel worked as a database reliability engineer at Slack for a little over 2 years and then for Cognite until he re-joined MongoDB. With over 15 years experience in software development and distributed systems, he is naturally curious and holds a Telecommunications Engineering MSc from Vigo University (Spain) and a Free and Open Source Software MSc from Rey Juan Carlos University (Spain).
Sequoyha Pelletier | Senior Technologist
Sequoyha Pelletier is a Senior Technologist at MongoDB, bringing over 15 years of experience in technical curriculum development and delivery. Before joining MongoDB, he worked in the Worldwide Support team for DataStax, eventually leading the curriculum team for new hire onboarding.
Sequoyha is extremely passionate about providing quality education for free to those in need and enjoys pushing the boundaries of what is considered "normal" practices with delivering educational content.
Colleen Day | Curriculum Designer
Colleen is a Curriculum Designer at MongoDB. She holds a Masters degree in English literature from NYU, and is passionate about using writing as a vehicle to teach. She has worked as a writing instructor and ghostwriter, and has spent her career focused on educational content development. For several years, Colleen was the lead editor for The Princeton Review’s “Cracking the SAT” and other test prep books. Prior to MongoDB, she was Senior Managing Editor for boot camp courses on data science and fintech, partnering with subject matter experts to design and deliver courses for learners of all levels.
Julianna Chen | University Curriculum Engineer
Julianna is a Senior Curriculum Engineer on the Education team, based in Vancouver, Canada. She’s developed educational content at universities and non-profits for over ten years, and is passionate about supporting access to quality technical education worldwide.
John McCambridge | University Curriculum Engineer
John is a Curriculum Engineer on the University team at MongoDB. Before his work as a Curriculum Engineer, he was an instructor and teaching assistant for coding boot camps at UT (Austin), and UCLA. Additionally, he worked as a QA engineer for a startup called Coder and spent five years at Apple Inc. John is a passionate software engineer and educator who enjoys taking complex topics and making them digestible for the community.
Davenson Lombard | Senior Software Engineer
Davenson Lombard is a Senior Software engineer at MongoDB on the Education Team. Prior to that, Davenson was a Technical Services Engineer at MongoDB and a Customer Success architect at Confluent. Davenson holds a Bachelor in Electrical Engineering from Concordia University in Montreal.
Welcome! If you’re here, you’ve heard about MongoDB and you’re curious to learn what sets it apart.
In this unit, we’ll cover the foundations you need to get started with MongoDB, from an overview of its architecture to a step-by-step walkthrough of MongoDB Atlas, our cloud-based data platform, where you'll create and deploy your first Atlas cluster.
But first, let's take a moment to discuss how databases developed historically. This will help us understand why MongoDB works in the way that it does.
In the early days of computing, mainframes were used to store and process data. They excel at transactions and batch processing, and many are still used for those purposes today. But they were also expensive to scale and difficult to maintain.
So in 1970, Edgar Codd developed the relational model. This was a new way of storing data through interlinked tables, where each piece of data was stored only once.
In order to store data without duplication, the relational model required a lot of upfront planning. Developers had to create a database schema and business logic before they could start using the database. This planning came with a huge benefit - relational databases saved on disk space at a time when storage was extremely expensive.
So, mainframes and relational databases each had their advantages. But with the adoption of the internet by the general public, there was an explosion of user generated data that relational databases and mainframes could not easily accommodate.
At the same time, the development of cloud computing meant that data storage costs drastically reduced. This new environment created an opportunity for a new kind of database. Enter, MongoDB!
MongoDB's document model stored data in a format that made communication and conversion to other web formats, like JSON and XML, easy.
Its flexible schema meant that developers wouldn't have to plan their data model in advance. They could store documents of different shapes and make adjustments and updates as needed, without downtime.
And finally, MongoDB allowed for horizontal scalability, so developers could quickly increase their storage space on the cloud as their apps grew.
In this environment, MongoDB emerged as a leading non-relational database, offering a flexible, scalable solution for managing data in modern applications.
In this unit, we’ll start by examining MongoDB's foundations. You'll learn that MongoDB is a distributed system. And you'll learn about MongoDB's document model which allows for a flexible schema.
Then we'll get into the architecture of MongoDB and cover key components that'll help you set up your first Atlas cluster.
We'll create an Atlas account and deploy our first cluster.
From there, we will load sample data and explore some of the built-in features of MongoDB Atlas.
This unit will set you up for success as you begin working with your data in MongoDB. Let’s get started!
