Stack Overflow Research of 100,000 Developers Finds MongoDB is the Most Wanted Database

Michael Lynn
March 13, 2018 | Updated: April 22, 2021

It’s well established that developers want to work with a database that offers flexibility, versatility, and ease of use. Scalability and reliability certainly don’t hurt either. For an increasing number of developers, MongoDB is the desired solution to meet all these requirements. And for the second year in a row, this has been validated by the opinions of those who matter most — developers themselves.

Today, we’re excited to announce that, for the second year in a row, MongoDB is the most wanted database in the Stack Overflow Developer Survey 2018, the world’s largest developer survey with over 100,000 respondents.

Steady Increases in Popularity

Since its debut, MongoDB’s popularity among developers has steadily increased. This popularity has been driven primarily by the platform’s ease of use and flexibility; more recently, the release of the fully managed database service MongoDB Atlas has made it easier than ever to run the database in any of the major cloud platforms.

MongoDB continues to innovate, listening and reacting to the demands of developers from small startups to the largest of enterprises. New and exciting features to the platform include change streams, which push real-time data updates to downstream applications, retryable writes, which enhance reliability without increasing complexity, and the announcement of multi-document ACID transactions, coming in version 4.0 later this year.

Why MongoDB?

MongoDB’s document model offers developers massive increases in productivity by allowing developers to store data in a way that is consistent with how they think and create applications. Additionally, MongoDB’s native replication and horizontal partitioning give developers the confidence and freedom to concentrate on differentiating code without having to be concerned about challenges associated with data locality, reliability and scalability. Lastly, MongoDB offers the freedom to run consistently all the way from local development environments to the largest mainframe deployments. The database can be deployed on-premises, in a hybrid cloud, or in any of the public clouds.

How can you benefit from this news?

Hiring managers seeking talented developers may do well to review some of the additional statistics included in today’s release. One interesting statistic can be found in the chart entitled “How Developers Assess Potential Jobs”. If you are a hiring manager and you’re looking to attract top talent, considering the most wanted database platform might be a way to enhance the attractiveness of your opportunities.

Javascript and Python developers reviewing the Stack Overflow report will be encouraged as these development environments continue to grow in popularity. Popularity of web application stacks like MEAN or MERN have provided Javascript developers with frameworks for building applications quickly.

Not using Javascript or Python? MongoDB offers full support for these and all popular development languages. Want to use Golang with MongoDB? A fully supported MongoDB Golang driver has reached Alpha stage in development, giving even more options to developers to build with the latest and most popular languages.

In summary

Developers are the new Kingmakers and their opinions are vitally important. The results of the Stack Overflow survey are an exciting validation of MongoDB’s efforts to build a resilient, flexible, and easy-to-use platform wanted by developers the world over.

Are you looking to learn more?

MongoDB University offers free courses for beginners, developers, database administrators, and operations personnel. Get online education about MongoDB Atlas, Compass and other products to help developers build great modern applications.

Want to build right away with MongoDB? Get started today with a 512 MB database managed by MongoDB Atlas here.

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Optimizing for Fast, Responsive Reads with Cross-Region Replication in MongoDB Atlas

MongoDB Atlas customers can enable cross-region replication for multi-region fault tolerance and fast, responsive reads. Improved availability guarantees can be achieved by distributing replica set members across multiple regions. These secondaries will participate in the automated election and failover process should the primary (or the cloud region containing the primary) go offline. Read-only replica set members allow customers to optimize for local reads (minimize read latency) across different geographic regions using a single MongoDB deployment. These replica set members will not participate in the election and failover process and can never be elected to a primary replica set member. In this post, we’ll dive a little deeper into optimizing for local reads using cross-region replication and walk you through the necessary configuration steps on an environment running on AWS. Primer on read preference Read preference determines how MongoDB clients route read operations to the members of a replica set. By default, an application directs its read operations to the replica set primary . By specifying the read preference, users can: Enable local reads for geographically distributed users. Users from California, for example, can read data from a replica located locally for a more responsive experience Allow read-only access to the database during failover scenarios A read replica is simply an instance of the database that provides the replicated data from the oplog; clients will not write to a read replica. With MongoDB Atlas, we can easily distribute read replicas across multiple cloud regions, allowing us to expand our application's data beyond the region containing our replica set primary in just a few clicks. To enable local reads and increase the read throughput to our application, we simply need to modify the read preference via the MongoDB drivers. Enabling read replicas in MongoDB Atlas We can enable read replicas for a new or existing MongoDB paid cluster in the Atlas UI. To begin, we can click on the cluster “configuration” button and then find the link named "Enable cross-region configuration options." When we click this, we’ll be presented with an option to select the type of cross-replication we want. We'll choose deploy read-only replicas : As you can see above, we have our preferred region (the region containing our replica set primary) set to AWS, us-east-1 (Virginia) with the default three nodes. We can add regions to our cluster configuration based on where we think other users of our application might be concentrated. In this case, we will add additional nodes in us-west-1 (Northern California) and eu-west-1 (Ireland), providing us with read replicas to serve local users. Note that all writes will still go to the primary in our preferred region, and reads from the secondaries in the regions we’ve added will be eventually consistent. We’ll click "Confirm and Deploy", which will deploy our multi-region cluster. Our default connection string will now include these read replicas. We can go to the "Connect" button and find our full connection string to access our cluster: When the deployment of the cluster completes, we will be ready to distribute our application's data reads across multiple regions using the MongoDB drivers. We can specifically configure readPreference within our connection string to send clients to the "closest replicas". For example, the Node native MongoDB Driver permits us to specify our preference: readPreference Specifies the replica set read preference for this connection. The read preference values are the following: primary primaryPreferred secondary secondaryPreferred nearest For our app, if we want to ensure the read preference in our connection string is set to the nearest MongoDB replica, we would configure it as follows: mongodb://admin: @cluster0-shard-00-00-bywqq.mongodb.net:27017,cluster0-shard-00-01-bywqq.mongodb.net:27017,cluster0-shard-00-02-bywqq.mongodb.net:27017,cluster0-shard-00-03-bywqq.mongodb.net:27017,cluster0-shard-00-04-bywqq.mongodb.net:27017/test?ssl=true&replicaSet=Cluster0-shard-0&authSource=admin?readPreference=nearest Security and Connectivity (on AWS) MongoDB Atlas allows us to peer our application server's VPC directly to our MongoDB Atlas VPC within the same region. This permits us to reduce the network exposure to the internet and allows us to use native AWS Security Groups or CIDR blocks. You can review how to configure VPC Peering here . A note on VPCs for cross-region nodes: At this time, MongoDB Atlas does not support VPC peering across regions. If you want to grant clients in one cloud region read or write access to database instances in another cloud region, you would need to permit the clients’ public IP addresses to access your database deployment via IP whitelisting . With cross-region replication and read-only replicas enabled, your application will now be capable of providing fast, responsive access to data from any number of regions. Get started today with a free 512 MB database managed by MongoDB Atlas here .

March 12, 2018
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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