Introducing the Certified MongoDB Atlas Connector for Power BI

Jad Jarouche and Mahesh Prakriya
May 23, 2023 | Updated: March 12, 2025
#Atlas

This is a collaborative post from MongoDB and Microsoft. We thank Alexi Antonino, Natacha Bagnard, Jad Jarouche from MongoDB, and Bob Zhang, Mahesh Prakriya, and Rajeev Jain from Microsoft for their contributions.

Introducing MongoDB Atlas Connector for Power BI, the certified solution that facilitates real-time insights on your Atlas data directly in the Power BI interfaces that analysts know and love!

Supporting Microsoft’s Intelligent Data Platform, this integration bridges the gap between Developers and Analytics teams, allowing analysts who rely on Power BI for insights to natively transform, analyze, and share dashboards that incorporate live MongoDB Atlas data.

Available in June, the Atlas Power BI Connector empowers companies to harness the full power of their data like never before. Let’s take a deeper look into how the Atlas Power BI Connector can unlock comprehensive, real-time insights on live application data that will help take your business to the next level.

Effortlessly model document data with Power Query

The Atlas Power BI Connector makes it easy to model document data with native Power BI features and data modeling capabilities. With its SQL-92 compatible dialect, mongosql, you can tailor your data to fit any requirements by transforming heavily nested document data to fit your exact needs, all from your Power Query dashboard.

Gain real-time insights on live application data

By using the Power BI Connector to connect directly to MongoDB Atlas, you can build up-to-date dashboards in Power BI Desktop and scale insights to your organization through Power BI Service with ease. With no delays caused by data duplication, you can stay ahead of the curve by unlocking real-time insights on Atlas data that are relevant to your business.

Empower cross-source data analysis

The Power BI Connector's integration with MongoDB Atlas enables you to seamlessly model, analyze, and share insightful dashboards that are built from multiple data sources. By combining Atlas's powerful Data Federation capabilities with Power BI's advanced analytics and visualization tools, you can easily create comprehensive dashboards that offer valuable insights into your data, regardless of where it is stored.

See it in action

Log in and activate the Atlas SQL Interface to try out the Atlas Power BI Connector! If you are new to Atlas or Power BI, get started for free today on Azure Marketplace or Power BI Desktop.

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4 Ways MongoDB Solves Healthcare's Interoperability Puzzle

Picture this: You're on a road trip, driving across the country, taking in the beautiful scenery, and enjoying the freedom of the open road. But suddenly, the journey comes to a screeching halt as you fall seriously ill and need emergency surgery. The local hospital rushes you into the operating room, but how will they know what medications you're allergic to, or what conditions you've been treated for in the past? Figure 1: Before and after interoperability In a perfect world, the hospital staff would have access to all of your medical records, seamlessly integrated into one interoperable electronic health record (EHR) system. This would enable them to quickly and accurately treat you as seen in Figure 1. Unfortunately, the reality is that data is often siloed, fragmented, and difficult to access, making it nearly impossible for healthcare providers to get a complete picture of their patients' health. That’s where interoperability comes in, enabling seamless integration of data from different sources and formats, allowing healthcare providers with easy access to the information they need, even between different health providers. And at the heart of solving the interoperability challenge is MongoDB, the ideal solution for building a truly interoperable data repository. In this blog post, we'll explore four ways why MongoDB stands out from all others in the interoperability software space. We'll show you how our unique capabilities make us the fundamental missing piece in the interoperability puzzle for healthcare. Let’s get started! 1. Document flexibility MongoDB's document data model is perfect for managing healthcare data. It allows you to work with the data in JSON format, eliminating the need to flatten or transform it into a string. This simplifies the implementation of common interoperability standards for clinical and terminology data, such as HL7 FHIR and openEHR, as well as SNOMED and LOINC - because all of these standards also support JSON. The document model also supports nested and hierarchical data structures, making it easier to represent complex clinical data with varying levels of detail and granularity. MongoDB's document model also provides flexibility in managing healthcare data, allowing for dynamic and self-describing schemas. With no need to pre-define the schema, fields can vary from document to document and can be modified at any time without requiring disruptive schema migrations. This makes it easy for healthcare providers to add or update information to clinical documents, such as when new interoperability standards are released, ensuring that healthcare data is kept accurate and up-to-date without requiring database reconfiguration or downtime. 2. Scalability Dealing with large healthcare datasets can be challenging for traditional relational database systems, but MongoDB's horizontal scaling feature offers a solution. With horizontal scaling, healthcare providers can easily distribute their data across multiple servers and cloud providers (AWS, GCP, and Azure), resulting in increased processing power and faster query times. It also results in more cost-efficient storage as growing vertically is more expensive than growing horizontally. This feature allows healthcare providers to scale their systems seamlessly as their data volumes grow while maintaining performance and reliability. While MongoDB’s reliability is ensured through its replication architecture, where each database replica set consists of three nodes that provide fault tolerance and automatic failover in the event of node failure. Horizontal scaling also improves reliability by adding more servers or nodes to the system, reducing the risk of a single point of failure. 3. Performance When it comes to healthcare data, query performance can make all the difference in delivering timely and accurate care. And that’s another aspect where MongoDB shines. MongoDB holds data in a format that is optimized for storage and retrieval, allowing it to quickly and efficiently read and write data. MongoDB’s advanced querying capabilities, backed by compound and wildcard indexes, make it a standout solution for healthcare applications. MongoDB Atlas’ Search, using Apache Lucene indexing, also enables efficient querying across vast data sets, handling complex queries with multiple fields. This is especially useful for Clinical Data Repositories (CDRs), which permit almost unlimited querying flexibility. Atlas Search indexing also allows for advanced search features enabling medical professionals to quickly and accurately access the information they need from any device. 4. Security Figure 2: Fine-grained access control The security of sensitive clinical data is paramount in the healthcare industry. That’s why MongoDB provides an array of robust security features, including fine-grained access control and auditing as seen in Figure 2. With Client-Side-Field-Level Encryption (CS-FLE) and Queryable Encryption, MongoDB is the only data platform that allows the processing of randomly encrypted patient data, providing the highest level of data security, with minimal impact on performance. Additionally, MongoDB Atlas supports VPC peering and private links that permit secure connections to healthcare applications, wherever they are hosted. By implementing strong security measures from the start, organizations can ensure privacy by design. Partner ecosystem MongoDB is the only non-relational database and modern data platform that directly collaborates with clinical data repository (CDR) vendors like Smile, Exafluence, Better, Firely, and others. While some vendors offer MongoDB as an alternative to a relational database, others have built their solutions exclusively on MongoDB, one for example is Kodjin FHIR server. MongoDB has extended its capabilities to integrate with AWS FHIR Works, enabling healthcare providers and payers to deploy a FHIR server with MongoDB Atlas through the AWS Marketplace. With MongoDB's unique approach to data storage and retrieval and its ability to work with CDR vendors, millions of patients worldwide are already benefiting from its use. Beyond interoperability with MongoDB Access to complete medical records is often limited by data silos and fragmentation, leaving healthcare providers with an incomplete picture of their patients' health. That's where MongoDB's interoperability solution comes in as the missing puzzle piece the healthcare industry needs. With MongoDB's unmatched document flexibility, scalability, performance, and security features, healthcare providers can access accurate and up-to-date patient information in real-time. But MongoDB's solution goes beyond that. Radical interoperability with MongoDB means that healthcare providers own the data layer and are thus able to leverage any usages from the stored data, and connect to any existing applications or APIs. They're free to work with any healthcare data standard, including custom schemas, and leverage the data for use cases beyond storage and interoperability. The future of healthcare is here, and with MongoDB leading the way, we can expect to see more innovative solutions that put patients first. If you're interested in learning more about radical interoperability with MongoDB, check out our brochure .

May 18, 2023

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What’s New From MongoDB at Google Cloud Next 2025

At Google Cloud Next '25, MongoDB is excited to celebrate a deepening collaboration with Google Cloud, focused on delivering cutting-edge solutions that empower developers, enterprises, and startups alike. The event comes as MongoDB Atlas adds availability for Google Cloud regions in Mexico and South Africa, further expanding joint customers’ ability to deploy, scale, and manage their applications closer to their users while meeting local compliance and performance requirements. MongoDB is also honored to have achieved the 2025 Google Cloud Partner of the Year for Data & Analytics - Marketplace. This award is a testament to the enterprise-scale success stories driven by our combined data and analytics solutions. It’s also MongoDB’s sixth consecutive year as a Google Cloud Partner of the Year, reflecting the relentless innovation and customer-first mindset that define MongoDB’s partnership with Google Cloud. This is in addition to achieving the Google Cloud Ready – Regulated and Sovereignty Solutions Badge. The designation is a major milestone for MongoDB, and demonstrates our ability to deliver compliant and secure solutions that meet the highest standards for data sovereignty. More broadly, we’ve been focused on expanding our collaboration in order to unlock new opportunities for customers to enhance developer productivity, launch AI-powered applications, and do more with their data in 2025. Read on to learn more about what we’ve been working on. Enhancing developer productivity with gen AI For over a decade, MongoDB and Google Cloud have established a rich track record of making it easier, faster, and more secure to build enterprise-grade applications. Our latest gen AI collaborations further this mission, simultaneously enhancing innovation and efficiency. MongoDB is proud to be a launch partner for Google Cloud’s Gemini Code Assist. Announced in December and launching for MongoDB users this week at Google Cloud Next, our integration with Gemini Code Assist enables developers to seamlessly access the latest MongoDB documentation and code snippets within their IDEs. This innovative integration enhances developer productivity by providing immediate access to MongoDB resources, making development workflows more efficient by keeping developers 'in the flow' rather than having to hop in and out of the IDEs to find the information and code examples they need. MongoDB is also expanding our presence in Project IDX , an AI-assisted development workspace for full-stack, multiplatform applications. With MongoDB templates now available in IDX, developers can quickly set up MongoDB environments without leaving their IDE, accelerating the development of generative AI applications and other cloud-based solutions. Learn more by reading this blog post from Google. Developers building applications in Firebase can now integrate MongoDB Atlas with a few clicks. The new Firebase extension for MongoDB Atlas eliminates the need for complex query pipelines or manual data transfers, making it easier than ever to deploy and scale apps leveraging MongoDB Atlas as a vector database in Firebase. Additionally, the new MongoDB extension enables real-time synchronization between Firebase and MongoDB data, ensuring data consistency across both platforms. By combining the power of Firebase Extensions, MongoDB Atlas, and a direct MongoDB connector, developers can create innovative and data-driven applications with greater efficiency and ease. Streamlining cloud migrations Developers are taking advantage of the latest models and tooling to build the next wave of gen AI applications. As they do so, they’re wrangling unprecedented volumes of structured and unstructured data, and, in doing so, are facing growing requirements for application scalability and performance. As such, businesses have uncovered a newfound imperative to modernize and take advantage of cloud-native solutions that offer the highest levels of scalability and performance, as well as interoperability with their favorite tools. MongoDB and Google Cloud have made it even easier to make the move to the cloud with Google Migration Center, a unified platform that streamlines the transition from on-premises servers to the Google Cloud environment, offering tools for discovery, assessment, and planning. Within Google Cloud Migration Center, users can now generate cost assessments and migration plans for the on-premises MongoDB instances directly in Google Cloud Migration Console, simplifying the transition to MongoDB Atlas on Google Cloud. Specifically, users can now use integrated MongoDB cluster assessment to gain in-depth visibility into MongoDB deployments, both Community and Enterprise editions, running on your existing infrastructure. Learn more on our blog . With the aim of making it easier and quicker to deploy to the cloud, MongoDB Atlas is now available as part of Cloud Foundation Fabric. Specifically, Atlas is available within Fabric FAST, which streamlines Google Cloud organization setup using a pre-defined enterprise-grade design and a Terraform reference implementation. By integrating MongoDB Atlas, enterprises can enhance production readiness for applications that require persistent data, offloading database management overhead while ensuring high availability, scalability, and security. This integration complements FAST’s infrastructure automation, enabling organizations to quickly deploy robust, data-driven applications within an accelerated Google Cloud environment, reducing the time needed to establish a fully functional, enterprise-level platform. Check out the Github repository . Optimizing analytics and archiving Despite many organizations’ focus on modernization and generative AI, analytics and data warehousing remain essential pillars of the enterprise workflow. Building on our existing integration with BigQuery, Google Cloud’s fully managed data warehouse, MongoDB Atlas now offers native JSON support for BigQuery, eliminating the need for complex data transformations. This enhancement significantly reduces operational costs, improves query performance, and enables businesses to analyze structured and unstructured data with greater flexibility and efficiency. The Dataflow template is now 'Generally Available' for MongoDB and Google Cloud customers. A key advantage of this pipeline lies in its ability to directly leverage BigQuery's powerful JSON functions on the MongoDB data loaded into BigQuery. This eliminates the need for a complex and time-consuming data transformation process as the JSON data within BigQuery can be queried and analyzed using standard BQML queries. Learn more about the new launch from our blog . In a big step forward for MongoDB, Atlas now supports Data Federation and Online Archive directly on Google Cloud. With these new additions, users can effortlessly manage and archive cold data and perform federated queries across Google Cloud storage, all from within their MongoDB Atlas console. This integration provides businesses with cost-effective data management and analysis capabilities. Upskilling for the AI era Earlier this year, MongoDB introduced a new Skill Badges program , offering focused credentials to help learners quickly master and validate their skills with MongoDB. These badges are an excellent way for developers, database administrators, and architects to demonstrate their dedication to skill development and continuous learning. In just 60-90 minutes, participants can learn new skills, finish a short assessment, and earn a shareable digital badge through Credly. They can then display this badge on platforms like LinkedIn to highlight their accomplishments and career development. At Google Next, attendees will have the opportunity to earn the RAG with MongoDB Skill Badge by using our self-paced Google Lab or by interacting directly with our experts in the Makerspace. This badge focuses on building Retrieval-Augmented Generation (RAG) applications, teaching participants how to integrate vector search and improve retrieval workflows to enhance apps powered by LLMs. Whether you prefer the guided support in the Makerspace or the flexibility of the self-paced lab, this hands-on experience will provide you with advanced skills that you can apply to your projects. The bottom line is that we’ve been busy! MongoDB’s deepening collaboration with Google Cloud continues to unlock new innovations across AI, application development, and cloud infrastructure. Stop by Booth #1240 at Google Cloud Next or join one of MongoDB’s featured sessions to explore these advancements and discover how MongoDB and Google Cloud are shaping the future of AI and data-driven applications. Head over to our MongoDB Atlas Learning Hub to boost your MongoDB skills.

April 9, 2025