DataGrip: a great database IDE to work with MongoDB Atlas

Massimiliano Marcon and Maxim Sobolevskiy
June 16, 2020 | Updated: September 9, 2024
#partners
>> Announcement: Some features mentioned below will be deprecated on Sep. 30, 2025. Learn more.

JetBrains released a new version of DataGrip that includes support for MongoDB and ships with the MongoDB Shell out of the box.

A few months ago, JetBrains released the first version of DataGrip that supports MongoDB. DataGrip is a professional DataBase IDE and is a great tool for advanced data exploration and analytical queries for your data in MongoDB and Atlas.

If you use any of the other JetBrains commercial products for development (e.g. IntelliJ, PhpStorm, PyCharm), you can install the Database Tools plugin and work with MongoDB right inside your IDE.

As we announced last week at MongoDB.live, the MongoDB plugin in DataGrip and in the other JetBrains IDE now includes a database console built on top of the MongoDB Shell. This is the result of a close collaboration between engineering teams at MongoDB and JetBrains and we are excited to finally release it to all our users.

With this integration, when you connect to MongoDB and Atlas with DataGrip, you get a console/shell experience that is 100% consistent with what you get in the terminal or in the other MongoDB’s developer tools.

DataGrip and Atlas

When your data is stored in Atlas, navigating through it with DataGrip is extremely easy.

For example, to connect to my free Atlas cluster, I can just grab a connection string from the Atlas UI, use it to add a new data source in DataGrip and I am connected and ready to explore my data.

Using Consoles

If you need to run queries, aggregations, or other database commands, consoles are a great way to do that.

The engineering teams at JetBrains and at MongoDB worked together to bring the new, embeddable MongoDB Shell to DataGrip and use it as the engine behind database consoles. This means the same commands that you can run in the MongoDB Shell are available in DataGrip and the other JetBrains IDEs and you can expect them to work exactly in the same way with the addition of the beautiful UI you are already used to on top.

Embedded MongoDB Shell

A great fit for Atlas Data Lake

DataGrip works well MongoDB deployments, whether self-managed or in Atlas. You can also use it with Atlas Data Lake. If you have data is stored in Amazon S3 and you want to query and analyze it with MQL, you can create a Data Lake and start working with it right away.

DataGrip’s search capabilities give you a quick way to find the data you are interested in, and its powerful export tool makes it easy to extract it in the format you need to use it with other tools like Excel, for example.

Get started with MongoDB Atlas and DataGrip

We are really happy with the result of our collaboration with the team at JetBrains and we are looking forward to working more together to bring all the future capabilities of the MongoDB Shell to DataGrip and the other JetBrains IDEs.

You can experience for yourself how DataGrip is a perfect companion for MongoDB Atlas:

  1. Get a free MongoDB Atlas cluster;
  2. Deploy some sample datasets;
  3. Download DataGrip and start working with your data immediately.
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MongoDB’s 2024 Year in Review

It’s hard to believe that another year is almost over! 2024 was a transformative year for MongoDB, and it was marked by both innovation and releases that further our commitment to empowering customers, developers, and partners worldwide. So without further ado, let’s dive into MongoDB’s 2024 highlights. We’ll also share our executive team’s predictions of what 2025 might have in store. A look back at 2024 MongoDB 8.0: The most performant version of MongoDB ever In October we released MongoDB 8.0 , the fastest, most resilient, secure, and reliable version of MongoDB yet. Architectural optimizations in MongoDB 8.0 have significantly improved the database’s performance, with 36% faster reads and 59% higher throughput for updates. Our new architecture also makes horizontal scaling cheaper and faster. Finally, working with encrypted data is easier than ever, thanks to the addition of range queries in Queryable Encryption (which allows customers to encrypt, store, and perform queries directly on data). Whether you’re a startup building your first app, or you’re a global enterprise managing mission-critical workloads, MongoDB 8.0 offers unmatched power and flexibility, solidifying MongoDB’s place as the world’s most popular document database. Learn more about what makes 8.0 the best version of MongoDB ever on the MongoDB 8.0 page . Delivering customer value with the MongoDB AI Applications Program AI applications have become a cornerstone of modern software, and MongoDB is committed to equipping customers with the technology, tools, and support they need to succeed on their AI journey. That’s why we launched the MongoDB AI Applications Program (MAAP) in 2024, a comprehensive program designed to accelerate the development of AI applications. By offering customers resources like access to AI specialists, an ecosystem of leading AI and tech companies, and AI architectural best practices supported by integrated services, MAAP helps solve customers’ most pressing business challenges, unlocks competitive advantages, and accelerates time to value for AI investments. Overall, MAAP’s aim is to set customers on the path to AI success. Visit the MongoDB AI Applications Program page or watch our session from AWS re:Invent to learn more! Advancing AI with MongoDB Atlas Vector Search In 2024, MongoDB further cemented its role in the AI space with enhancements to MongoDB Atlas Vector Search . Recognized in 2024 (for the second consecutive year!) as one of the most loved vector databases , MongoDB continues to provide a scalable, unified, and secure platform for building cutting-edge AI use cases. Recent advancements like vector quantization in Atlas Vector Search help deliver even more value to our customers, enabling them to scale applications to billions of vectors at a lower cost. Head over to our Atlas Vector Search quick start guide to get started with Atlas Vector Search today, or visit our AI resources hub to learn more about how MongoDB can power AI applications. Search Nodes: Performance at scale Search functionality is indispensable in modern applications, and with Atlas Search Nodes, organizations can now optimize their search workloads like never before. By providing dedicated infrastructure for Atlas Search and Vector Search workloads, Search Nodes ensure high performance (e.g., a 40–60% decrease in query times), scalability, and reliability, even for the most demanding use cases. As of this year , Search Nodes are generally available across AWS, Google Cloud, and Microsoft Azure. This milestone underscores MongoDB’s commitment to delivering powerful solutions that scale alongside our customers’ needs. To learn more about Search Nodes, check out our documentation or watch our tutorial . Looking ahead: MongoDB’s 2025 predictions After the excitement of the past few years, 2025 will be defined by ensuring that technology investments deliver tangible value. Organizations remain excited about the potential AI and emerging technologies hold to solve real business challenges, but are increasingly focused on maintaining a return on investment. “Enterprises need to innovate faster than ever, but speed is no longer the only measure of success. Increasingly, organizations are laser-focused on ensuring that their technology investments directly address critical business challenges and provide clear ROI and competitive advantage—whether it’s optimizing supply chains, delivering hyper-personalized customer experiences, or scaling operations efficiently,” said Sahir Azam, Chief Product Officer at MongoDB. “In 2025, I expect to see organizations make significant strides in driving this innovation and efficiency by applying AI to more production use cases and by maturing the way they leverage their data to build compelling and differentiated customer experiences.” Indeed, we expect to see organizations make more strategic investments in emerging technologies like gen AI—innovating with a sharp focus on solving business challenges. “In 2025, we can expect the focus to shift from ‘what AI can do’ to ‘what AI should do,’ moving beyond the hype to a clearer understanding of where AI can provide real value and where human judgment is still irreplaceable,” said Tara Hernandez, VP of Developer Productivity at MongoDB. “As we advance, I think we’ll see organizations begin to adopt more selective, careful applications of AI, particularly in areas where stakes are high, such as healthcare, finance, and public safety. A refined approach to AI development will be essential—not only for producing quality results but also to build trust, ensuring these tools genuinely support human goals rather than undermining them.” With more capable, accessible application development tools and customer-focused programs like MAAP at developers’ fingertips, 2025 is an opportunity to make a data-driven impact faster than ever before. "Right now, organizations have an opportunity to leverage their data to reimagine how they do business, to more effectively adapt to a changing world, and to revolutionize our quality of life,” said Andrew Davidson, SVP of Products at MongoDB. “By harnessing our latest technologies, developers can build a foundation for a transformative future." Head over to our updates page to learn more about the new releases and updates from MongoDB in 2024. Keep an eye on our events page to learn what's to come from MongoDB in 2025!

December 19, 2024