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So now, it's finally time

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to get started writing some MongoDB code

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or running some MongoDB queries.

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And as you'll see,

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that will be quite different to what we did

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in the SQL world.

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When it came to working with SQL and MySQL,

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we started by setting up a database and then some tables,

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and we started by setting up the structure of our table.

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Now, here with MongoDB, it will be quite different.

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If we wanna insert some data, if we wanna store some data,

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we don't need to set up any table at all,

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simply because, with MongoDB,

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or with NoSQL databases in general, as you learned,

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the idea of having a fixed structure

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with predefined data types just doesn't exist.

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Instead, as you learned,

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the idea is that you have these collections

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with documents inside of them,

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and that you can have different documents

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with different structures in one of the same collection.

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Now, in reality, you will typically end up

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with similarly structured documents in the same collection,

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but you simply don't have a fixed predefined structure

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for your documents in a collection.

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So therefore, with MongoDB,

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we don't start by setting up tables or collections,

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or by defining some structures,

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we can just start by inserting some data.

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As a first step though,

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we have to select a database

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into which we wanna select data.

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And we ran the show dbs command

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to see which databases we have.

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But these three databases,

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which are listed here out of the box for me,

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are all built-in databases that store some system data

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in some configuration,

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and we therefore don't wanna use them

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for our application data.

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Instead, what we wanna do here

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is we wanna use a new database.

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And for this, we can run the use command here.

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Simply type use,

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and then the database name you wanna work with.

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And as an example for this section,

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I'll come back to an example I used

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in the SQL introduction section,

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where we had Restaurants and Reviews,

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simply because there I showed you how you would store

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that kind of data with SQL.

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Now, I think it's great

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to understand how we would store that with NoSQL.

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But again, we'll not start with the full example here.

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We'll come to that later in this section,

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instead I wanna start with the basic CRUD operations.

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And hence, we'll just have a look

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at some dummy Restaurants data that we might wanna store

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in a Restaurants collection.

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So first of all, we need a database as mentioned,

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and we can use the use command for this,

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and then a fitting database name.

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So not a collection name for the restaurants,

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but the name for a database

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that might hold multiple collections related

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to restaurants and reviews.

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It could be ratingportal,

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because maybe we're building a portal for users

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to leave ratings.

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So now you can hit Enter, and that's all.

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As you can tell,

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we now switched to this new database here.

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And of course, that wasn't the database we had before,

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but by simply using it, it was created for us.

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You still don't see it if you run show dbs,

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because it will actually only really be created

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once you start inserting some data into a collection

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in that database.

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But switching to it is the first step for doing so.

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Now once you've switched,

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you can start inserting data.

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Because as I mentioned,

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you don't need to create a table or collection to do so,

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instead it will be created on the fly

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if you simply insert data.

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Now to insert data into a collection,

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we write db to refer to the currently active database.

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And then, we need to tell MongoDB

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into which collection we wanna insert data.

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For example, the restaurant's collection.

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So you just type the restaurants collection

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after a dot after db.

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Now, this collection doesn't exist yet,

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but just like the database, it will be created on the fly

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once we insert data.

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And as a side note,

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this already looks a lot like JavaScript.

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db.restaurants, that looks

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like we always access properties on JavaScript objects

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throughout this course, with this dot notation.

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And indeed, there is a lot of similarity.

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The MongoDB query language,

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which we are using here,

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is based on JavaScript, you could say,

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but it's really important to understand

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that this is a specific language written

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by the MongoDB team, or created by the MongoDB team,

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understood by the MongoDB server

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that really can only be used with MongoDB.

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Because that's a key difference compared

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to SQL-based database systems.

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Whereas SQL is a generally standardized language

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that works with all SQL-based database systems,

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NoSQL database systems

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typically bring their own query language.

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So this language here works with MongoDB only in the end,

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but the documentation

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of the different database engines is really good in the end

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and it's all straightforward

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to pick up those query languages.

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So here, with that, we access a collection

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on the database we are currently using,

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and then we can type another dot and now execute a bunch

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of methods, you could say, to run queries

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against this collection in this database.

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For example, the insertOne method.

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And again, this looks just like JavaScript.

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We're now executing this method on this collection.

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And as the name suggests,

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insertOne can be used to insert data,

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one piece of data, to be precise, into this collection.

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There also is a insertMany command

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in case you wanna bulk insert data,

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and insert multiple documents at once.

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But we're going to get started in a simple way here

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and just insert one document.

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And then, a document just looks like a JavaScript object

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with opening and closing curly braces.

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And between those curly braces,

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you can now have your key value peers.

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For example, for the restaurant, we can have a name.

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So we can add such a name field here.

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You can come up with any keys you want.

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And that name here could be a string created

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with double quotes, for example, "Munich Schnitzelhouse".

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And here, we already see our first data type,

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which you can use:

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a string created with quotes, just as in JavaScript.

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There also are the other data types you would expect,

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like numbers, or also dates, or also nested data types,

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like erase or nested objects.

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Because as I mentioned before in this section already,

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that's a specialty of NoSQL database systems,

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that you can have nested structured data

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instead of splitting your normalized flat data

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across multiple tables, as you would do it with SQL.

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So having nested data would be totally normal here.

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And indeed, we can already add our first piece

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of nested data here.

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Besides adding the name, we could add an address field here,

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because every restaurant should also have an address,

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and that now could indeed be some structured document.

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So another pair of curly braces,

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where we store the address for this specific restaurant

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as a sub-document, you could say,

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with more key value fields.

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For example, here, we could have the street,

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and that could be "Some Street 5".

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And then, separated by a comma,

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here we could also then have the street number,

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and that could be an actual number 25,

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or to support things like 23b,

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we could also make it a string again.

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Now here, I automatically have a line, a break,

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because I ran out of space in that first line,

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but it's still one command here.

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And with that, we could insert such a restaurant.

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Now, we'll come back to the question

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of whether it's a good idea to store the address

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as a nested object instead of a standalone document

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in a standalone collection,

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but for the moment that's the kind

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of restaurant I wanna store.

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And we can now hit Enter to send this command

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to the MongoDB server to which we're connected.

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And as a response,

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we get this kind of answer here,

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where we get the ID of the inserted document,

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because MongoDB will automatically create a unique ID

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for every document that's inserted.

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So that's kind of similar to SQL-based databases,

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where we also had unique IDs.

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We also have them here.

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They just look different.

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In the end, they are long, unique strings generated

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by the MongoDB server.

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And with that, our data is stored.

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Now let's add a second piece of data.

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And for this, I'll just quickly duplicate that command

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from before and switch the data, "Another Street".

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I just noticed I had a street number here in my first piece

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of data already.

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It doesn't matter too much.

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It's just an example.

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Of course, it should have been stored

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in this separate street number.

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So I've fixed this here in the second document,

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where I didn't add an extra number in the street here.

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And then, we can also go back here and change the name

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to "Burger House".

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I'm really creative here, as you can tell.

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And hit Enter to insert this as well.