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Redis can be used as an event hub instead of a storage database. This is done in tandem with another database used for storage. This is helpful because it helps with separating the logic of storing data according to different events. See More
Usually the way Redis works is this: the client sends a request to the server and waits for a response which is returned from the server once the request is executed. This can obviously bring performance issues when trying to issue multiple commands though. Redis mitigates this through a technique called pipelining. The way this works is: you send commands to the server in sequence and the Redis client then receives the combined responses in a single block once the pipeline is closed. See More
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The content is deployed immediately through the Firebase CLI. Once it's uploaded, the content is served immediately. If you have made a mistake, you don't need to re-upload a new version, through the Admin dashboard you can easily rollback to a previous version. See More
MongoDB queries can be very fast because the data is usually all in one place and can easily be retrieved in a single lookup. But this is true only when the data is truly a document. When it's trying to emulate a relational model it starts to become really slow because it may have to perform many independent queries to retrieve a single document. See More
MongoDB has powerful sharding and scaling capabilities for when the data stored in the database gets so large that a single machine may not be able to store all of it. Sharding solves this problem through horizontal scaling. Mongo gives developers the ability to easily and painlessly add or remove as many machines as needed. See More