This section provides comprehensive guidance for developing applications with MongoDB. Learn how to connect to MongoDB, perform CRUD operations, use the query language, optimize with indexes, and design effective data models.
This section of the documentation covers core MongoDB features and capabilities applicable to both self-managed deployments and MongoDB Atlas, including database fundamentals, streaming data processing, and release notes for the latest product updates.
Database Manual
- Overview
- An overview of MongoDB and its features.
- Documents
- Documents are the basic unit of data storage in MongoDB. Learn how MongoDB stores and structures data as BSON documents.
- Databases and Collections
- Databases and collections are used to organize documents in MongoDB. Learn how to create and manage databases and collections.
- Client Libraries
- MongoDB provides official client libraries for various programming languages. Learn how to use these libraries to interact with MongoDB in your applications.
- Connect to Clusters
- Learn how to connect to your Atlas or self-managed MongoDB deployment.
- Database Users
MongoDB uses database users to authenticate clients. You can grant database users different roles to control their access to the database and dictate what actions they can perform.
Learn how to create and manage database users in both Atlas and self-managed deployments.
- CRUD Operations
- Learn how to create, read, update, and delete documents in collections.
- Indexes
- Indexes support efficient query execution in MongoDB. Learn how to create and manage indexes to optimize query performance.
- Data Modeling
- Data modeling refers to the organization of data within a database and the links between related entities. Learn how to design your data model to best suit your application's needs.
- Aggregation Operations
- Use aggregation pipelines to processes documents and return computed results. Learn how to use aggregation operations to analyze and transform your data.
- Search
- is an embedded full-text search that gives you a seamless, scalable experience for building relevance-based app features. Learn how to get started with and implement advanced search capabilities in your applications.
- Vector Search
- By using MongoDB as a vector database, you can use to seamlessly search and index your vector data alongside your other MongoDB data. Learn how to implement vector search in your applications.
- AI Integrations
- Learn how to integrate MongoDB with AI frameworks, tools, and platforms to build AI applications and agents.
- Time Series
- Time series data is a sequence of data points that lets you analyze changes over time. Learn how to create and manage time series collections and work with time series data.
- Change Streams
- Change streams let applications access and respond to real-time data changes. Learn how to configure change streams to respond to changes in data.
- Transactions
- Transactions allow you to perform multiple read and write operations across one or more documents as a single atomic operation. Learn how to use transactions in your application and client library.
- Data Federation
- Data Federation lets you query data across multiple data sources, including S3, Atlas clusters, and other MongoDB databases. Learn how to set up and use Data Federation in your applications.
- In-Use Encryption
- In-use encryption secures data when transmitted, stored, and processed, and enables supported queries on that encrypted data. Learn about the different approaches to in-use encryption in MongoDB and how to use them in your applications.
- Development Checklist
- Learn best practices for developing MongoDB applications for production workloads including data durability, schema design, and scaling.
- Replication
- Replication provides data redundancy and high availability by having multiple MongoDB instances. Learn what replication is, how it works, and the components and architecture of replica sets.
- Sharding
- Sharding distributes data across multiple servers to support deployments with large data sets and high throughput operations. Learn how sharding works and the components and architecture of sharded clusters.
- Performance
- Analyze MongoDB performance by examining database access strategies, indexing, schema design, and connection management to address potential issues.
- Reference
- Reference documentation for MongoDB commands, operators, and configuration options.
- Support
- Access technical support through MongoDB Community Forums, Cloud account, or Support Portal for various MongoDB services.
Streaming Data
Learn how to work with streaming data in MongoDB Atlas.
- Atlas Stream Processing
- Atlas Stream Processing lets you read, write, and transform streams of complex data using aggregation operations. Learn how to create and manage stream processing jobs in Atlas.
- Atlas Triggers
- Atlas Triggers let you execute server-side logic in response to database events or on a scheduled basis. Learn how to create and manage triggers in Atlas.
Release Notes
Learn about the latest changes and improvements in MongoDB products.
- Server Release Notes
- Release notes for the MongoDB server.
- Atlas Release Notes
- Release notes for MongoDB Atlas and related services.
- Search Release Notes
- Release notes for MongoDB Search.
- Vector Search Release Notes
- Release notes for MongoDB Vector Search.