Today, we’re delighted to announce that we’ve doubled the concurrent connections limit for the Firebase Realtime Database from 100k to 200k. This takes effect today, for all existing databases and new projects. And while this level of scalability will be enough for the majority of projects out there, some of you might want to support even more concurrent users. For that, you might want to consider sharding your database.

Many kinds of apps can scale much higher by sharding their data across multiple Realtime Database instances in a single project. The 200k concurrent user limit applies to each individual database, so the total number of concurrent connections increases linearly as you add more instances.

Sharding is a good strategy to employ when each client interacts with isolated parts of the database. Imagine a virtual whiteboard app, which is the sort of high-frequency, low-latency collaboration app for which the Realtime Database really excels. Whiteboard sessions don’t interact with each other — just with the handful of users that are drawing together. So they can be sharded across an unlimited number of instances. When multiple users create a session, your app could assign that session to a random shard; then the clients only need to be connected to that database in order to receive their realtime updates.

Most IoT apps can also take advantage of sharding. If you want to have a gigantic number of tiny sensors sending periodic updates, they probably don’t all need to write to the same RTDB instance. You can create lots of shards (we support up to 1000), and assign each sensor to a shard. If you’re interested in working with multiple versions of the Realtime Database in the same project, make sure to check out our documentation.

Of course, if you’re looking for a powerful realtime database that scales without sharding, we still recommend our newer database, Cloud Firestore, for most new projects. It has the same magical realtime, offline, serverless functionality as the Realtime Database, but has been architected for higher reliability, has more powerful queries, and locations around the world.

Nonetheless, there are some use cases for which the Realtime Database is the right choice, even for new applications. That’s why we’re continuing to invest in making it even better for these purposes.

When should you pick the Realtime Database for a new project? The short answer is that if you are building an application that will have lots of tiny operations, the Realtime Database may be less expensive and more performant. For the whiteboarding app, you’d want to send lots of frequent little updates as the users draw on the whiteboard, and you’d want latency to be as low as possible. In the IoT case, performance may not be as important, but the Realtime Database may end up cheaper than Cloud Firestore if you are sending a massive stream of tiny writes.

Of course, you can use both Cloud Firestore and the Realtime Database together in the same project — we encourage it! For instance, you can use the Realtime Database to power the live whiteboard feature, but then persist the whiteboard contents to Firestore periodically to take advantage of its 99.999% availability and less expensive storage.

We hope you are excited about the increased scaling capabilities of the Realtime Database. And we also hope this guidance helps you decide between Cloud Firestore and the Realtime Database for new projects. As always if you have any questions, feel free to reach out on StackOverflow, or the firebase-talk discussion group.