19 Creating Atlas charts, database triggers, and functions

This chapter introduces how MongoDB Atlas helps you turn operational data into insight and automation. It starts with Atlas Charts, a no‑code visualization layer tightly integrated with MongoDB that lets you explore trends, spot anomalies, and communicate results through shareable dashboards. It then broadens to Atlas Application Services, showing how database triggers and serverless functions let you react to data changes in real time, orchestrate workflows, and connect to external systems without managing infrastructure.

Atlas Charts supports direct connections to collections, views, and purpose-built charts views, handling nested documents and arrays while leveraging aggregation for rich analysis. You can build many chart types, embed them in apps, and even generate visuals from plain‑English prompts, which Atlas converts into aggregation pipelines. Natural Language charts may send your prompt, schema metadata, and sampled values to a managed AI service to improve recommendations, but credentials are never transmitted and original prompts may be retained for service quality purposes. The chapter also shows how to track cloud costs with customizable billing dashboards, and explains pricing for Charts based on data transferred to browsers, including a monthly free allowance and per‑GB overage. Charts works across Atlas cluster configurations, including dedicated, Flex, Online Archive, and Data Federation sources.

On the automation side, Atlas Application Services provides three trigger types—database, scheduled, and authentication—each wired to an Atlas Function that executes your server-side JavaScript. Database triggers are powered by change streams and can be scoped from collection to deployment, filtered with match/project expressions, and configured to process events in order or at high concurrency; the chapter outlines capacity, throughput considerations, and optimization tactics. It walks through creating a trigger, capturing full documents or preimages, and common patterns like auditing, data synchronization, enforcing business rules, calling external APIs, or enriching documents (for example, storing embeddings). Atlas Functions run in a managed, scalable environment with context about the caller, access to MongoDB data, HTTP utilities, and Node.js modules, making them a lightweight way to implement validation, transformation, notifications, and other short‑running tasks.

This example of Atlas Chart includes the total number of movies (2,658) and their average Metacritic score (55). The 'Movie Ratings' pie chart breaks down films by rating categories. The 'Top 10 Genres' bar chart highlights the most popular genres, with drama leading. The 'Top 10 Languages' chart shows that English dominates, while the 'Most Prolific Actors' chart identifies actors with the most appearances, categorized by critic ratings (Fresh, All-Rated, Rotten)

The chart generated using MongoDB Atlas's Natural Language Mode based on a plain English query. The chart displays a borough-wise breakdown of the top 10 cuisines by the number of restaurants. The y-axis lists the cuisines, while the x-axis shows the count of restaurants (restaurant_id). Each borough is represented by different colors (along with restaurants that are missing a designation). The chart highlights that American cuisine has the highest presence, particularly in Manhattan.

The Atlas billing dashboard with three main financial metrics on the left: total spend for the month to date is $23.80, total spend for the previous month is $25.42, and total spend for the year to date is $98.42. The central chart visualizes daily spending across various projects over the past week, with each project contributing to the total spend on each day, represented by different colored segments in the bars. Filters on the right side allow for further customization of the data displayed.

The trigger types in Atlas: Database Triggers (Insert, Update, Delete, Replace), Scheduled Triggers (Basic, Advanced), and Authentication Triggers (Create, Login, Delete).

The Add Trigger interface in MongoDB Atlas. At the top, you can choose the trigger type: Database or Scheduled. In the Trigger Details section, you can set the trigger's name, enable or disable it, choose to skip events when re-enabled, and control event ordering.

The MongoDB Atlas interface for setting up a scheduled trigger. The "Trigger Type" is set to "Scheduled," indicating that this trigger will execute at regular intervals. The name of the trigger is specified in the "Name" field. The "Schedule Type" is set to "Advanced," which allows for complex scheduling using CRON expressions. CRON expressions provide flexibility by allowing you to define exactly when the trigger should run.

• Atlas Charts is a MongoDB Atlas tool for creating and sharing visualizations like bar charts and line graphs directly from your MongoDB data. It offers a no-code interface, real-time data updates, and seamless integration with MongoDB, allowing you to embed charts into applications or dashboards for easy data analysis. It offers Natural Language, Column and Bar ChartsLine and Area, Combo Heatmaps, Scatter, Donut, Gauge, Tables, Number, Word, Top Item, Geospatial.
• Natural Language Charts uses Azure OpenAI, but this may change. MongoDB sends your query, schema, and sample data to its backend and the AI provider, without sharing credentials or data with third parties. Queries are stored for up to a year to improve service and support.
• With Atlas Charts, you can easily create a billing dashboard to visualize your billing data. These dashboards include ready-made charts that help you monitor your usage. After loading your billing data, you can customize the dashboard to meet your requirements.
• Atlas Application Services are managed backend services and APIs that simplify building cloud apps. They let you respond to MongoDB Atlas data changes, integrate with other systems, and scale easily, without server or infrastructure management.
• There are three types of Atlas triggers: Database for changes in a MongoDB collection, Scheduled for recurring tasks, and Authentication for user interactions with authentication providers. Each trigger is connected to a specific Atlas Function. When the trigger detects an event that meets your defined criteria, it "fires." It then passes the event object as an argument to the associated function.
• Database triggers are highly effective mechanisms for automating processes and enforcing rules without requiring manual input. They react to data changes and ensure that the stored information adheres to established standards and complies with specific business rules.
• Database triggers utilize MongoDB change streams to track real-time changes in a collection. A change stream is made up of a series of events, each describing an action taken on a document within the collection.
• Scheduled triggers enable you to execute server-side logic at predefined intervals. They are ideal for tasks that need regular execution, such as updating a document every hour, generating a daily performance report, or processing routine data analysis.
• Authentication triggers are triggered by events related to user authentication, such as login, account registration, or account deletion. For example, when a user registers a new account, an authentication trigger can be used to send a welcome email or automatically subscribe the user to a mailing list.
• An Atlas function is server-side JavaScript code that controls your app's behavior. It can be run directly from the client app or triggered automatically. These functions can call other functions, access MongoDB Atlas data, and use built-in tools.
• Atlas functions can call other functions, access data in MongoDB Atlas clusters using a built-in client, and support global utilities, Node.js modules, and external npm packages.

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