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Mongodb Data Model Diagram. However we can stretch the concept to fit JSON documents. Now you know how to do that. This flexibility gives you data-modeling choices to match your application and its performance requirements. As mentioned there the ERD is simply a mapping of the data you intend to store and the relations amongst that data.
However we can stretch the concept to fit JSON documents. The big difference is that MongoDB has no joins so when you translate the ERD into an actual schema youll have to make some specific. For Data Modeling with MongoDB Key Considerations. Dataedo discovered entities and their fields. There are multiple ways to model time-series data in a document database such as MongoDB such as one document per data point or bucketing data points into one document per minute. Moon Modeler is a visual database design tool for both relational and noSQL databases.
Consider the following diagram.
The question you refer to provides more information about how to use UML for MongoDB. I would model the schema as a UML class diagram. Collections do not enforce document structure by default. One of the most important steps in building data-intensive apps is to actually model all this data in MongoDB and so thats what were gonna talk about in this tutorial about data modeling. These schema are generally known as denormalized models and take advantage of MongoDBs rich documents. Data Modeling Introduction An introduction to data modeling in MongoDB.