Hyperscale with HiveMQ: Learn About Scale From Our 200 Million Benchmark

Today we’re thrilled to announce the release of a new benchmark report, Achieving 200 Million Concurrent Connections with HiveMQ, to show senior technology leaders how we achieved 200 million concurrent connections with the HiveMQ MQTT Platform. Whether you need to make 1,000, 10 million or 200 million connections for your mission-critical business application, the same best practices for IoT scalability apply. Let’s talk about why scale matters, what the benchmark achieved, and what you can learn from this industry-leading feat to deploy and scale your IoT projects successfully.

Why Scale Matters

The proliferation of Internet of Things (IoT) devices continues to escalate, with over 14 billion connected devices today, equating to nearly 2 per person on the planet. Despite this growth, there is still a great deal of untapped potential. The imminent adoption of advanced IoT standards and connectivity presents a unique opportunity for businesses to continue to innovate and scale. A significant portion of the global population remains unconnected, many businesses are still working to digitally transform, and new connected products are being developed at a rapid pace. The sky is truly the limit when it comes to growth.

At the same time, scaling challenges threaten progress. Those include data silos, inconsistent data formats, and the inability to securely move data between edge and cloud systems. If there was ever a time to think about solving these problems to scale IoT, it’s now.

The key is building the right data foundation that will allow you to move any amount of data to power new use cases, new products and services, and new locations. Each of these initiatives requires an infrastructure that can support new data connections and lays a future-proof foundation for IoT deployments.

HiveMQ is an MQTT Platform that has established itself as a proven solution for reliable, scalable, mission-critical IoT, with the capability to handle tens of millions of connected devices and concurrent connections. We see more customers coming to us with this need for scale, while simultaneously demanding high reliability and performance. To support this need, our team benchmarked the HiveMQ platform at 200 million connections to demonstrate our ability to handle extreme scale.

The 200 Million Benchmark

The HiveMQ team created an installation based on projected real-world requirements like computing infrastructure and storage on a hyperscale cloud (AWS), using a pub/sub architecture with a skewed ratio and a clustered system for resilience. The benchmark test allows us to observe, document and share how the broker can meet scaling expectations with the MQTT protocol and the HiveMQ broker.

Highlights:

• Gradual and even ramp up to 200 million connections in 37 minutes

• 20 million publishers connecting to 180 million subscribers over 200 million unique MQTT topics

• Peak message throughput of 1 million PUBLISH messages per second

• Real-world scenario using commercially available public infrastructure with publicly available products from HiveMQ (Broker and Swarm)

• Workload was contained to a single installation to test the true performance of the broker cluster

The results of our benchmark test on the HiveMQ broker demonstrates its ability to meet the demands of the growing IoT ecosystem. Download the complete benchmark report for the technical details of how 200 million connections were achieved.

Building a Data Foundation for Scale

While not every company will need to make 200 million connections, and while some may need even more, the same basic principles apply. You must choose a data movement platform that is flexible, reliable, and easy to scale so your architecture will grow with you and allow you to reap the full benefits of IoT.

There are three critical considerations companies working to deploy and scale IoT projects can learn from the successful HiveMQ 200 million benchmark.

1. Load test before deploying into production. Many customers think the small POC phase is enough without using a distributed simulation environment to successfully test millions of clients and messages. As a result, they truly don’t know how the deployment will behave. Load testing for performance, scalability, and reliability ensures success.

2. Plan for scale. There are two types of projects. One is already large, for instance connecting all 115 million smart electricity meters in the US, or offering services for the 13 million+ connected vehicles sold in the US since 2021. The other starts small but plans for growth as new services, devices, and sites are added, for instance a consumer goods manufacturing company with plans to add 20 factories. In both cases, it is essential to support growth from the onset by planning for scale.

3. Architecture matters. In this test, the clustered architecture provided by the HiveMQ MQTT broker makes it ultra-scalable and highly available. Clustering is typically used in cloud environments for systems that must not fail and need linear scalability over time. While the MQTT protocol has its inherent benefits, it’s not built for extreme scale by itself and a premium MQTT broker like HiveMQ is essential.

The long-term success of your business depends on the ability to scale. Thanks to the benchmark you know MQTT can help and HiveMQ is available to support you along the entire journey whether you start small or require enterprise-level scale and reliability. Contact us to download the HiveMQ broker and build a data foundation for your project that can scale to any size. You can also email us at benchmarking@hivemq.com if you are interested in talking about how you can run this kind of test yourself.