MongoDB Named a Leader in 2022 Gartner® Magic Quadrant™ for Cloud Database Management Systems

Vivek Bhalla
January 10, 2023

MongoDB is proud to be named a Leader in the 2022 Gartner® Magic Quadrant for Cloud Database Management Systems (DBMS). We believe this achievement makes MongoDB the only pure-play application database provider recognized as a Leader.

Here at MongoDB, we feel the true achievement is not in the placement, rather the means by which it was achieved. At MongoDB we strive to offer engineering teams an enhanced approach through a unified developer data platform as opposed to contending with multiple disparate and fragmented technologies and products. Our desire is to give customers a single cohesive design philosophy with a consistent workflow, API, data model, query language, management and navigation through this unified data developer platform. This design is flexible enough to service almost any application - so significantly reduces cognitive toil engineering teams have to deal with. Therefore, teams can build and release faster, evolving their apps at higher velocity than competitors. We believe that this philosophy has been validated, not only by the community of developers that have built up around MongoDB, but now by this placement in this publication from Gartner.

Based on our conversations with customers, we don’t think that having a tool for every job makes sense because over time, the tax and cost of learning, managing and supporting those different tools doesn’t make a lot of sense or just becomes cost-prohibitive.¹
Dev Ittycheria, MongoDB CEO - November 2022

Cloud Database Management Systems are defined by Gartner as “Core capabilities are that vendors fully supply provider-managed public or private cloud software systems that manage data in cloud storage. Data is stored in a cloud storage tier. Optionally, they may cater to multiple data models and data types — relational, nonrelational (document, key value, wide column, graph), geospatial, time series and others.”

To help users understand this emerging technology landscape, Gartner published its first Cloud Database Management Systems Magic Quadrant back in 2020. Two years on and after an evolving criteria, Gartner has named MongoDB as a Leader in its debut as a qualifying vendor for the latest 2022 Magic Quadrant.

We believe MongoDB was named a Leader in this report due to the R&D investments made in further building out capabilities in MongoDB Atlas, our multi-cloud developer data platform.

These investments were driven by the demands of the developer communities we work with. You told us how you struggle to bring together all of the data infrastructure needed to power modern digital experiences – from transactional databases to analytics processing, full-text search, and edge computing. This is exactly what our developer data platform offers. It provides an elegant, integrated, and fully-managed data architecture accessed via a unified set of APIs.

With MongoDB Atlas, developers are more productive, they ship code faster and improve it more frequently.

Cloud native - First and foremost

Virtually every organization we work with at MongoDB has a cloud strategy. It's not zero sum, so there are some apps that will never go there. However, everyone is either using or looking to use the cloud because of the agility it brings to them. MongoDB delivers this to our customers via a fully managed, cloud-native document-based database; MongoDB Atlas, our globally distributed developer data platform. This platform easily and securely reduces time spent on development cycles and empowers organizations with flexible schema and the tools they need to innovate.

MongoDB Atlas’ multi-cloud clusters take the concept a step further by enabling a single application to use multiple clouds simultaneously. With multi-cloud clusters, data is easily distributed across different public clouds, like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. This enables data mobility and resilience without the complexity of manual data replication. This philosophy was taken a stage further earlier this year with the delivery of our serverless architecture. This abstracts away server, storage, and network provisioning, plus the management overhead. Thus, organizations and their development teams can focus on building differentiating features and creating great app experiences for their customers.

Such expanding product vision was called out by Gartner as a notable strength. The authors of the magic quadrant recognised our plans to deliver more comprehensive analytics support and SQL capabilities alongside the existing functionality delivered to date. These additions have extended the document data model to embrace time series, application search and application-driven analytics use cases among others, and deliver an industry proven multi-model general purpose operational and transactional database.

The community of MongoDB users have also spoken on Gartner Peer Insights™; 97% of MongoDB users who provided reviews to Gartner Peer Insights platform said they would recommend us ² (based on 36 ratings in the last 12 months, as on December 21, 2022).

Customer review from an anonymous user providing MongoDB with a 5 star rating. The review reads as follows: MongoDB is a superb open-source management information system that is completely free. It makes it easier than ever to work with significant quantities of dispersed data. It's an extremely fast, scalable, resilient, transparent, and highly operational database. Querying MongoDB is quite easy and has a very quick learning curve. It is extremely efficient and reads data correctly in real-time. Using this tool, running complex queries has become a breeze, and information processing has become lightning quick. Because of its NoSQL features, it can store data in a Data Source, which allows it to hold information with dynamic attributes. A straightforward terminology is used to write the question.

Evaluating a leader in the Magic Quadrant for cloud database management systems

Gartner evaluated 20 of the most significant cloud DBMS vendors against 15 criteria (7 on execution and 8 on vision). These criteria span current product offering, market responsiveness and record through to innovation and the business model.

Our rapid adoption in the past decade and move to cloud was highlighted by Gartner as a strength. It is our opinion that our placement as a Leader in this Magic Quadrant is an acknowledgement of this.

Visit the Gartner website to obtain the full report here (requires Gartner subscription)³.

Customer momentum

Organizations frequently start their journey with MongoDB by employing it as an operational database. This can be for both, new cloud-native services, as well as modernized legacy apps. Both scenarios are routinely enhanced by appending application search, mobile and analytics use cases to the core operational database requirement. Increasingly more diverse teams are now improving customer experience and attaining business agility by embracing what the MongoDB community have become accustomed to for years. Examples include:

Forbes for migration to the cloud in six months
Verizon for pioneering 5G connectivity and data storage to the edge
Powerledger for legacy data platform migration

Getting started on your Cloud journey

MongoDB Atlas is engineered to help you make the shift to the cloud. We can come in to understand more about your key transformation initiatives and workshop ideas with your teams to accelerate delivery. In the interim, your engineers and developers can familiarize themselves with MongoDB right away by signing up for a free account on MongoDB Atlas. Have them create a free database cluster, load your own data or our sample data sets, and explore what’s possible within the platform.

From November 2022, we have enhanced the MongoDB learning experience. The updated program includes an expanded catalog of courses, streamlined developer certifications, 24/7 exam access, hands-on Atlas labs, and foreign language support. Additionally, the MongoDB Developer Center hosts an array of resources including tutorials, sample code, videos, and documentation.

¹Source: SiliconANGLE article, 28th November 2022: “MongoDB’s Dev Ittycheria on how the cloud is expanding developers’ influence”, Mike Wheatley

² Gartner® and Peer Insights™ are trademarks of Gartner, Inc. and/or its affiliates. All rights reserved. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

³Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. The Gartner logo is a trademark and service mark of Gartner, Inc., and/or its affiliates, and is used herein with permission. All rights reserved.

← Previous

Securing Multi-Cloud Applications with MongoDB Atlas

The rise of multi-cloud applications offers more versatility and flexibility for teams and users alike. Developers can leverage the strengths of different cloud providers, such as more availability in certain regions, improved resilience and availability, and more diverse features for use cases such as machine learning or events. As organizations transition to a public, multi-cloud environment, however, they also need to adjust their mindset and workflows — especially where it concerns security. Using multiple cloud providers requires teams to understand different security policies, and take extra steps to avoid potential breaches. In this article, we’ll examine three security challenges associated with multi-cloud applications, and explore how MongoDB Atlas can help you mitigate or reduce the risks posed by these challenges. Challenge 1: More clouds, more procedures, more complexity Security protocols, such as authentication, authorization, and encryption, vary between cloud providers. And, as time goes on, cloud providers will continue to update their features to stay current with the market and remain competitive, adding more potential complications to multi-cloud environments. Although there are broad similarities between AWS, Azure, and GCP, there are also many subtle differences. AWS Identity and Access Management (IAM) is built around root accounts and identities, such as users and roles. Root accounts are basically administrators with unlimited access to resources, services, and billing. Users represent credentials for humans or applications that interact with AWS, whereas roles serve as temporary access permissions that can be assumed by users as needed. In contrast, Azure and GCP use role-based access control (RBAC) and implement it in different ways. Azure Active Directory allows administrators to nest different groups of users within one another, forming a hierarchy of sorts — and making it easier to assign permissions. However, GCP uses roles , which include both preset and customizable permissions (e.g., editor or viewer), and scopes , or permissions that are allotted to a specific identity concerning a certain resource or project. For example, one scope could be a read-only viewer on one project but an editor on another. Given these differences, keeping track of security permissions across various cloud providers can be tricky. As a result, teams may fail to grant access to key clients in a timely manner or accidentally authorize the wrong users, causing delays or even security breaches. Challenge 2: Contributing factors Security doesn’t exist in a vacuum, and some factors (organizational and otherwise) can complicate the work of security teams. For example, time constraints can make it harder to implement or adhere to security policies. Turnover can also create security concerns, including lost knowledge (e.g., a team may lose its AWS expert) or stolen credentials. To avoid the latter, organizations must immediately revoke access privileges for departing employees and promptly grant credentials to incoming ones. However, one study found that 50% of companies took three days or longer to revoke system access for departing employees, while 72% of companies took one week or longer to grant access to new employees. Challenge 3: Misconfigurations and human error According to the Verizon Data Breach Investigations Report , nearly 13% of breaches involved human error — primarily misconfigured cloud storage. Overall, the Verizon team found that the human element (which includes phishing and stolen credentials) was responsible for 82% of security incidents. Because misconfigurations are such common mistakes, they comprise the majority of data breaches. For example, AWS governs permissions and resources through JSON files called policies. However, unless you’re an expert in AWS IAM, it’s hard to understand what a policy might really mean. Figure 1 shows a read-only policy that was accidentally altered to include writes through the addition of a single line of code, thereby inadvertently opening it to the public. That data could be sensitive personally identifiable information (PII); for example, it could be financial data — something that really shouldn’t be modified. Figure 1: Two examples of read-only policies laid out side by side, demonstrating how a single line of code can impact your security. Although the Verizon report concluded that misconfigurations have decreased during the past two years, these mistakes (often AWS S3 buckets improperly configured for public access) have resulted in high-profile leaks worldwide. In one instance, a former AWS engineer created a tool to find and download user data from misconfigured AWS accounts . She gained access to Capital One and more than 100 million customer credentials and credit card applications. The penalties for these vulnerabilities and violations are heavy. For example, the General Data Protection Regulation (GDPR) enacts a penalty of up to four percent of an organization’s worldwide revenue or €20,000,000 — whichever is larger. In the aftermath of the security event, Capital One was fined $80 million by regulators ; other incidents have resulted in fines ranging from $35 million to $700 million . Where does MongoDB Atlas come in? MongoDB Atlas is secure by default, which means minimal configuration is required, and it’s verified by leading global and regional certifications and assurances. These assurances include critical industry standards, such as ISO 27001 for information security, HIPAA for protected healthcare information, PCI-DSS for payment card transactions, and more . By abstracting away the details of policies, roles, and other protocols, Atlas centralizes and simplifies multi-cloud security controls. Atlas provides a regional selection option to control data residency, default virtual private clients (VPCs) for resource isolation, RBAC for fine-tuning access permissions, and more. These tools support security across an entire environment, meaning you can simply configure them as needed, without worrying about the nuances of each cloud provider. Atlas is also compatible with many of the leading security technologies and managers, including Google KMS, Azure Key Vault, or AWS KMS, enabling users to either bring their own keys or to secure their clusters with the software of their choice. Additionally, data is always encrypted in transit and at rest. For example, you can run rich queries on fully encrypted data using Queryable Encryption , which allows you to extract insights without compromising security. Data is only decrypted when the results are returned to the driver — where the key is located — otherwise, encrypted fields will display as randomized ciphertext. One real-world example involves a 2013 data breach at a supermarket chain in the United Kingdom, where a disgruntled employee accessed the personal data of nearly 100,000 employees. If Queryable Encryption had been available and in use at the time, the perpetrator would have downloaded only cipher text. With MongoDB Atlas, securing multi-cloud environments is simple and straightforward. Teams can use a single, streamlined interface to manage their security needs. There is no need to balance different security procedures and structures or keep track of different tools like hyperscalers or key management systems. Enjoy a streamlined, secure multi-cloud experience — sign up for a free MongoDB Atlas cluster today .

January 9, 2023

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