We use it in a few ways. Sometimes it functions as a cache for quick lookups using scans. Other times, DocumentDB serves as a complete backend. For example, we built the entire backend of one of our healthcare applications for Sweden using DocumentDB. We store patient records, medical information... everything runs on DocumentDB.
Its speed has had the most significant impact on our projects. For starters, we used it for its flexibility. With DocumentDB, you're not tied to a rigid structure like you are with Aurora or other relational databases. This makes it great for startups. When we work with established systems where the structure is well-defined, the speed of DocumentDB becomes the most important factor. Compared to a relational database, scaling DocumentDB is easier because of its ability to replicate data across different instances. If you use a network-based storage service with your cluster, the primary instance doesn't even need a full local copy of the data, since it's accessible on the shared storage. That definitely contributes to scalability. AWS-managed services already handle a lot of the scaling complexity. We don't have to do anything.
