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MongoDB Part-1 (Introduction)

What is MongoDB?

• MongoDB is a NO-SQL database.
• Managed by the company that is also known as MongoDB.
• The name mongo comes from the word humongous because we can store and analyze a huge amount of datasets.
• In MongoDB, we have databases inside that databases we have collections, i.e. similar to tables that we have in SQL.
• In each collection we have a set of documents, documents are the JSON, objects, or dictionary whatever you want to call them. Eg-> {“name” : “Utkarsh”}
• MongoDB is schemaless, i.e. no two documents are required to have the same fields. That’s what makes it a Non-Relational Database.

• JSON object consists of key-value pairs, where the key will be of type string and value can be string number or a nested object.
• By having nested objects we can have many sub-documents inside a single document.
• {‘name’ : ‘Utkarsh’, ‘address’ : { ‘city’ : ‘Kanpur’, ‘post’ : { ‘number’ : 208001 }}} here you can see in one document we are having many documents.
• By this nested functionality we can avoid the complex queries of SQL like joins and all, and can directly fetch the result.
• In the backend the JSON data is stored as BSON data, BSON means Binary JavaScript Object Notation.
• BSON helps in reducing the size of data and increasing the speed of data transactions.

Characteristics Of MongoDB

• MongoDB is very flexible in terms of data storage since it is schemaless so we need to worry about the structure to be followed.
• MongoDB supports Indexing making it very fast for the read operations.
• MongoDB follows master-slave relation that helps in data security and replication.
• GeoSpatial queries are supported in MongoDB.
• Load Balancing is done with the help of shards(sharding).
• Horizontal scaling is also supported.
• Map Reducers and Aggregation queries are supported.
• Regex searches and ad-hoc queries are very easy to use.

Installation and Connection

• We can directly download MongoDB from their official website and use their community version or you can also go for paid versions.
• For this blog, I have used the MongoDB cloud to host my database there only.
• We will be using the free cluster that is provided by MongoDB.

• Once you create your cluster it will look something like this.
• For practice purposes, you can use the dummy dataset provided by MongoDB itself.
• Once you add that dataset then your database will look something like this.

• In the sample dataset, we are going to have around 8 databases with 21 collections that are a very good dataset for testing and practicing purposes.
• Now for the hands-on and querying purposes, we are going to use Robo3T for the visualization and analysis of our dataset.
• It can be directly downloaded from their official website, once downloaded we can put our mongo connection string there and connect to it.
• After connection, it will look something like this.

• Now we are all done with the connections and installations so let’s get our hands dirty.

Basic Commands use in MongoDB

• To check the databases – show dbs

• To check the collections- show collections

• To use a particular database- use db_name
• By default admin, config and local databases are present.
• For creating a database you are not required to use any command you can just type use <your_db_name>, it will create a database for you.
• Similary for the collections you can directly write db.collectionName.insertOne({‘key’ : value})
• Else you can use db.createCollection(collectionName, {capped : true, size :3071400, max :1000})
• The capped keyword is used when we want to restrict the document from the updates when the updates result in a size greater than the original one.
• Max keyword is used to allow the maximum number of documents in a collection.
• for dropping a collection db.collectionName.drop()
• for dropping the database you can go inside that by using dbName and then run db.dropDatabase()

• for finding or searching a document in a collection we directly write db.collection.find({}), for the specific value we can pass the key-value pair inside the find.

Conclusion

• In this part, we have covered the basics of MongoDB.
• In the upcoming parts, we are going to cover the CRUD operations as well as aggregation and complex queries.

References-

• https://docs.mongodb.com/

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