guarantee response within specified time constraints to specific events. These time constraints depend from the kind of application you are developing. Self-driving cars are one of the most amazing example of real-time applications. The have really strict time constraints… otherwise you will be dead.
real-time too. I believe in a good messaging application a message should go from UserA to UserB within 100 ms. Facebook built a really cool scalable mobile-first infrastructure for Messenger capable to send a message from one user to another in under 100 ms. FB Messenger is clearly a good example of real-time chat messaging application.
receive a lightweight message (maybe over web sockets) indicating new data is available, and then it sends the server a more complicated http request asking for the data. Push-based approach. The client first retrieves an initial snapshot of the data (generally with an http request) and then subscribes to delta updates, which are immediately pushed to the app (maybe through MQTT).
API, and a server- side runtime for executing queries by using a type system you define for your data. GraphQL isn't tied to any specific database or storage engine and is instead backed by your existing code and data.
(e.g. web, iOS, Android) that render data differently • You may have to care about latency and bandwidth, especially in real-time applications • You may want to quickly decouple front-ends and back-ends GraphQL allows each client to query exactly what it needs, in the format it needs. It is the clean layer of abstraction between servers and clients that an ad-hoc REST approach will never be able to provide.
package. It also has two fantastic modules call mqtt- connection and mqtt. All of them available on npm. It is easier to use these three libraries together to build a fully working Node.js application.