Understand how SQL terminology and concepts correspond to MongoDB terminology.

Follow step-by-step instructions for getting set up on MongoDB Atlas. Learn how to create an Atlas cluster, connect to it, and load sample data.

Learn the fundamentals of using MongoDB Atlas, including the document model, connections, indexing, administration, and monitoring via the UI and CLI.

Learn the fundamentals of document databases, why they are a popular alternative to relational databases, and how to leverage MongoDB Cloud to build modern, data-driven applications.

Learn more about a flexible schema model and why data modeling is important on MongoDB.

Learn how to use Atlas monitoring tools to find common schema design issues and get suggestions for modifications.

Follow the foundational steps of creating an effective data model in MongoDB.

Examine the most important considerations when deciding on your data model and create the best model for your application.

Get an overview of common SQL aggregation terms, functions, and concepts and the corresponding MongoDB aggregation operators.

Learn how aggregation operations process multiple documents to compute results, allowing you to group values, perform operations on grouped data, and analyze data changes over time.

Learn how to create aggregation pipelines that enable you to analyze and summarize data by stringing together stages that filter, sort, group, and/or transform data.

Watch how MongoDB's aggregation framework in Python enables increasingly complex queries to group, join, limit, skip, and bucket data.

Learn how indexes support efficient execution of queries in MongoDB and how to get started in Atlas, driver method, or with the MongoDB Shell.

Learn how to improve MongoDB performance by creating single, compound, and multikey indexes as well as deleting indexes.

Understand the essentials of MongoDB indexes—what they are, how they work, and how to use them to boost database efficiency.

Understand the significance of index configuration in MongoDB’s Atlas Search and how it impacts the searchability and effectiveness of queries.

Read how to power Atlas Search in MongoDB Atlas to give you a seamless, scalable experience for building relevance-based app features.

Learn how to use Atlas Vector Search to enable semantic querying of data in Atlas, supporting AI-powered use cases like semantic, hybrid, and generative search while integrating with AI frameworks.

Learn how to achieve a seamless full-text search experience with Atlas Search, powered by Apache Lucene.

Explore how to use Atlas Search to search through different data types, including text, numbers, dates, and geoJSON and discover a variety of search capabilities.

Explore how to use the MongoDB Relational Migrator free tool to help you migrate data from a relational database to MongoDB.

Learn how to easily migrate data to Atlas from MongoDB, JSON, or CSV using live migration or self-guided tools.

Learn how to migrate data from a MongoDB deployment on any environment to an Atlas deployment using the Live Migration feature.

Learn how the Relational Migrator tool simplifies app modernization by converting relational databases to optimized MongoDB structures using AI-powered features.