👉In this article, we are discussing two databases, MongoDB and PostgreSQL. We are going to cover their key features, functionality, performance, and their use cases.
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#mongodb tutorial #mongodb tutorial for beginners #mongodb database #mongodb with c# #mongodb with asp.net core #mongodb
NoSQL databases gained massive popularity in recent years. Rather than storing everything in row and column values, NoSQL databases provide more flexibility. There are quite a few document-oriented NoSQL databases available like AWS SimpleDB, MongoDB, and others. MongoDB provides more flexibility and operations than other NoSQL cloud databases. This would be a series of articles containing information on how to create a MongoDB cluster for cloud databases, how to create collections, and do Create, Read, Update and Delete (CRUD) operations through MongoDB compass (GUI) or through Python (pyMongo). Furthermore, future articles will also contain some advanced operations. If you already know how to create a MongoDB cluster and connect to it through MongoDB compass GUI, you can ignore this article and go to the next one.
First of all, you need to create an account in MongoDB, it’s completely free and does not require credit card information to get MongoDB atlas. You can register through here. MongoDB Atlas provides the cloud database. Once you register, you can select the cluster you want. There are three options available, the one we will use is shared cluster since it’s great for small projects and learning purposes, and it is free. As the name suggests, it will be a shared cluster while other clusters provide more advanced and dedicated services.
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#mongodb #mongodb database #mongodb tutorial for beginners #mongodb with asp.net core #mongodb with c#
Perform queries across multiple MongoDB databases and collections, where the field names and the field content structure in each database may vary.
Suppose you’ve got two database collections, “leak1” and “leak2”
leak1, the schema looks like this:
FIRST_NAME: "JOHN" LAST_NAME: "DOE"
leak2, the schema looks like this:
FName: "John" LName: "Doe"
A simple program to iterate through all your collections and perform queries wouldn’t work, because:
leak1, the first name field is
FIRST_NAME, while in
leak2, the first name field is named
leak1, everything is captialized. In
leak2, it’s all title-case.
This program lets you write a configuration for each collection, specifying, in JSON, how to query each field.
It’s a work in progress, but so far, it works pretty well. It’ll probably be easier to understand if you take a look at the config files under
./collections/. Each JSON file under
./collections/ should be an array of objects. The program automatically processes all JSON files under that directory.
Some more info for how the configurations work can be found in the wiki.
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