Introducing the MongoDB Atlas Data API, Now Available in Preview

Emma Lullo and Sumedha Mehta
November 18, 2021 | Updated: September 9, 2024

>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more.

As the leading data platform, MongoDB is hyper-focused on accelerating and simplifying how developers leverage their application data. This has led to the introduction of features like serverless instances and the Atlas Triggers that minimize the operational burden associated with traditional database workloads.

Today, we’re excited to announce the next step forward in this mission with the introduction of the MongoDB Atlas Data API – a fully managed, REST-like API for accessing your Atlas data. The Data API makes it easy to perform CRUD and aggregations on your data in minutes and allows you to query MongoDB from your backend in any language, without the need for drivers.

The next level of data access

Organizations are increasingly relying on operational data layers to build distributed architectures like microservices for their modern applications to speed-up development and stay competitive in rapidly changing markets. These stacks often require scalable, highly available, and secure access to the data layer.

The most popular way to architect these data services is to build APIs that communicate with MongoDB data over HTTPS using REST or similar protocols. However, creating a custom-built API typically takes a lot of time and effort. It's a painful process that introduces unnecessary operational burdens like provisioning additional servers, connection management, and scaling.

With the Atlas Data API, customers can generate a fully managed, REST-like API for their Atlas data in seconds. Developers no longer need to worry about the underlying infrastructuring of their APIs, and instead can enjoy the efficiency of intuitive, out-of-the box data access, while still being able to leverage the always-on and highly available qualities of Atlas as the underlying database.

This unlocks a whole new level of developer productivity for use cases that were previously time consuming to accomplish – such as building data-centric microservices, simplifying access from serverless functions, and integrating with third party services . The API even has built-in support for aggregation pipelines to use with services like Atlas Search.

Try the Atlas Data API

All customers now have the ability to enable the Data API for their Atlas deployment. We invite you to try it out today with a new or existing Atlas account.

It’s incredibly easy to get started: simply choose the cluster you’d like to connect to and generate an API key. That’s all it takes to set up and start accessing Atlas data.

Have questions? Check out our documentation or head over to our community forums to get answers from fellow developers.

What's next for the Atlas Data API

This preview release is just the beginning. Support for services like Data Lake and Serverless Instances will be added over the coming months. And, long term, we see the Data API as the next step in our journey to abstract and automate infrastructure decisions – to help developers build the future faster.

Atlas Data API documentation can be found here

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Simplifying Compliance with VComply & MongoDB

As businesses globally are facing external pressures to be more focused on privacy, security, and transparency, compliance management is needed now more than ever. With 200+ regulatory updates, 900 regulatory agencies, and the average cost of a non-compliance incident being $14 million, maintaining compliance is critical for every business, no matter the size. Tracking, maintaining, and proving compliance has traditionally been incredibly difficult, resource-intensive, and takes a significant time commitment. That's why one startup aims to simplify compliance by disrupting the antiquated industry. Enter VComply . Founded in 2019, VComply is a governance, risk management, and compliance (GRC) platform that enables its customers with a secure and easy-to-use solution. VComply is highly configurable to meet the specific needs of any organization without additional coding or infrastructure changes. The platform collects, organizes, analyzes, and automatically reports on GRC data inputted into the system to provide a high-level view of an organization's compliance posture at any given time. Combining that with the ability to surface detailed information on any control, VComply modernizes how people work and interact with GRC programs within their businesses. In this week's #BuiltWithMongoDB, we take a look at VComply to learn more about how they are truly helping organizations strengthen their risk and compliance management. We spoke with Harshvardhan Kariwala, CEO, and Ashish Jha, Vice President of Engineering at VComply to discuss the company's journey and how they decided to build with MongoDB. What inspired you to build the business? Harshvardhan: VComply is actually my third startup. At one of my previous companies, I had become hyper-focused on building the business, and I eventually lost sight of compliance. Operational functions fell through the cracks, and I ended up outsourcing our compliance programs to this corporate firm in Singapore. Fast forward a bit, they ended up forgetting to do a required compliance filing, and we ended up responsible for paying the non-compliance fines associated with that. One reporting misstep, and we were fined. That's what got me worried. We got lucky that was all that happened. It only took one time to inspire action. We then built an internal tool where the entire idea was around creating a culture of reporting excellence and internal accountability. After adopting our newly created tool, in 2018, we realized that we built a very robust solution to real day-to-day compliance problems. We thought, "Why don't we spin this off into its own product?" By that time, I was ready to get back into product development, and this was the perfect opportunity. In early 2019 we set up VComply. We quickly got our first customer, the City of Boston, and never looked back. So that's where VComply got its start. It was never meant to be sold as a product. It was more of an internal compliance tracking tool. That's how we entered the GRC space. What exactly does VComply do? What are some of its most useful product features? Harshvardhan: We help businesses be compliant, mitigate risk, and adopt a culture of transparency. If there isn't internal alignment within a company, no tool is going to help them. At its core, VComply is designed to be easy to use so that anyone in an organization can adopt a compliance-first mindset. By removing the traditional technological barriers, we found that businesses can realize the benefits quickly. That said, VComply serves as the single source of truth for everything GRC within an organization. Think tracking compliance obligations, compliance monitoring, automating activities, alerts and follow-ups, compliance evidence collection, audit trails, and more. Another popular piece of our tool is our enterprise risk management as well as policy management functionalities. You can monitor and manage risk programs, quickly identify risks, and start linking compliance obligations to mitigate that risk. What makes VComply stand out from its competitors? Harshvardhan: Most other solutions on the market require a compliance expert, are hard to navigate, and take a significant time commitment upfront to get up and running. We built VComply to be more practical and realistic with how people manage their compliance and risk programs today. VComply is easy to set up, simple to use for the end-user, and flexible to map to the specific controls a business needs to comply with without any additional coding. How did you decide to build with MongoDB? Ashish: Easy and intuitive search support, as well as indexing and automated performance suggestions, were the key drivers for us building with MongoDB. Also, training new developers is very straightforward. What has your experience been like scaling with MongoDB? Ashish: Scaling is pretty seamless with MongoDB. Setting up alerts and monitoring is very straightforward. We've had nothing but great experiences so far. Do you have a favorite technical book or podcast that you would recommend to other tech entrepreneurs? Harshvardhan: I would recommend The Great CEO Within: The Tactical Guide to Company Building by Matt Mochary. That's definitely a great read. This is a bit of an open questions, so feel free to interpret it how you'd like. What are you currently learning? Harshvardhan: That's a tough one. I think you're always learning so many different things on any given day that it's difficult to give one answer. Today, I'm learning marketing strategies, like demand gen as well as sales tactics to scale the business. Ashish: Primarily, I'm learning how engineering can augment and support other organizations within the company. Who are some tech leaders or entrepreneurs that you admire? Ashish: I do admire Jeff Bezos quite a bit. I admire the laser focus that he has and the clarity in terms of his reasoning. Harshvardhan: Elon Musk because of his ideas and execution. One thing that's great about him is how he executes his ideas flawlessly. Interested in learning more about MongoDB for Startups? Learn more about us here .

November 17, 2021

Next →

MongoDB Database Observability: Integrating with Monitoring Tools

This post is the final in a three-part series on leveraging database observability. Welcome back to our series on Leveraging Database Observability! Our previous post showcased a real-world use case highlighting how MongoDB Atlas’s observability tools effectively tackle database performance challenges. Whether you’re a developer, DBA, or DevOps engineer, our mission is to empower you to harness the full potential of your data through our observability suite . Integrating Atlas metrics with your central enterprise observability tools can simplify your operations. By seamlessly working with popular observability tools, our approach helps teams streamline workflows and enhance visibility across systems. Integrating MongoDB Atlas with third-party monitoring tools MongoDB’s developer data platform combines all essential data services for building modern applications within a unified experience. Our purpose-built observability tools for Atlas environments offer automatic monitoring and optimization, guiding diagnostics tailored specifically for MongoDB. Additionally, we extend Atlas metrics into your existing enterprise observability stack, enabling seamless integration without replacing your current tools. This creates a consolidated, single-pane view that unifies Atlas telemetry with other tech and application metrics, ensuring comprehensive visibility into both database and full-stack performance. This integration empowers you to monitor, receive alerts, and make data-driven decisions within your existing workflows, driving greater efficiency. Below is a quick guide to modifying integration settings through the Atlas UI and the popular integrations we support: Navigate to the Project Integrations page in Atlas. Choose the organization and project you want to configure from the navigation bar. On the Project Integrations page, select the third-party services you’d like to integrate. Configure the chosen services with the required API keys and regions. Critical integrations for your observability platform With Atlas’s Datadog and Prometheus integrations, you can send critical MongoDB metrics to these platforms, empowering detailed, real-time monitoring. Through Datadog , you can track database operation counts, query efficiency, and resource usage, ideal for pinpointing bottlenecks and managing resources. Similarly, Prometheus enables you to monitor essential metrics like query times, connection rates, and memory usage, supporting flexible tracking of database health and performance. Both integrations facilitate proactive detection of issues, alert configuration for resource thresholds, and a cohesive view of Atlas data when visualized in Grafana. Atlas’s integration with PagerDuty streamlines incident management by sending metrics like performance alerts, billing anomalies, and security events directly to PagerDuty. This integration records incidents automatically, notifies teams upon alerts, and supports two-way syncing, ensuring resolved alerts in Atlas are reflected in PagerDuty. It enables efficient incident response and resource allocation to maintain system stability. With Atlas integrations for Microsoft Teams and Slack, you can route key metrics—such as query latency, disk usage, and throughput—to these channels for timely updates. Teams can use these insights for real-time performance monitoring, incident response, and collaboration. Notifications through these platforms ensure your team stays informed on database performance, storage health, and user activity changes as they occur. Use case: Centralized observability with MongoDB Atlas, Datadog, and Slack Let’s walk through a hypothetical scenario for ShopSmart, an e-commerce company that leverages MongoDB Atlas to manage its product catalog and customer data. As traffic surges, the DevOps team faces challenges in monitoring application performance and database health effectively. To tackle these challenges, the team leverages MongoDB Atlas’ integration with Datadog and Slack, creating a powerful observability ecosystem. Integrating MongoDB Atlas with Datadog: The team pushes key MongoDB Atlas metrics into Datadog, such as query performance, connection counts, and Atlas Vector Search metrics. With Datadog, they can visualize these metrics and correlate overall MongoDB performance with their other applications. Out-of-the-box monitors and dedicated dashboards allow the team to track metrics like throughput, average read/write latency, and current connections. This visibility helps pinpoint bottlenecks in real time, ensuring optimal database performance and improving overall application responsiveness. Setting up alerts in Datadog: The team configures alerts for critical metrics like high query latency and increased error rates. When thresholds are breached, Datadog instantly notifies the team. This proactive approach allows the team to address potential performance issues before they impact customers. Integrating Datadog with Slack: To ensure fast communication, alerts are sent directly to the dedicated Slack channel, “ShopSmart-Alerts.” This integration fosters seamless collaboration, enabling the team to discuss and resolve issues in real-time. With these integrations, ShopSmart’s engineering team can monitor performance quickly and address issues efficiently. The unified observability approach enhances operational efficiency, improves the customer experience, and supports ShopSmart’s competitive edge in the e-commerce industry. By leveraging MongoDB Atlas, Datadog, and Slack, the team ensures scalable performance and drives continuous innovation. Conclusion MongoDB Atlas empowers developers and organizations to achieve unparalleled observability and control over their database environments. By seamlessly integrating with central enterprise observability tools, Atlas enhances your ability to monitor performance metrics and ensures you can do so within your existing workflows. This means you can focus on building modern applications confidently, knowing you have the insights and alerts necessary to maintain optimal performance. Embrace the power of MongoDB Atlas and transform your approach to database management—because your applications can thrive when your data is observable. And that wraps up our Leveraging Database Observability series! We hope you learned something new and found value in these discussions. Sign up for MongoDB Atlas , our cloud database service, to see database observability in action. To dive deeper and expand your knowledge, check out this learning byte for more insights on the MongoDB observability suite and how it can enhance your database performance.

November 14, 2024