If you are here then I take the responsibility of taking you from being a beginner to that level where you can fluently make your own database schemas. I will first set up a pattern for you. If you don't understand all then no worries because it's just to build your mental patterns. Having these patterns will help you to better understand and learn faster.

I really suggest you to give 4 to 5 minutes just staring at the cycle for the understanding with flow🙃.

If you find this hard just don't get overwhelmed!😯

content:

1: Installing MongoDB, Shell, compass, and MongoDB tools
2: Introduction to MongoDB
3: MongoDB Atlas & Compass
4: Comparing SQL and NoSQL Databases
5: JSON vs BSON
6: Database & Collections Management within MongoDB
7: Ordered and Unordered Insert Operations
8: CRUD operations
9: Indexing
10: Aggregation Framework

1: Installing MongoDB, Shell, compass, MongoDB tools

Installing MongoDB is not easy as installing other applications such as VS Code, MySQL or other SDK. So, do this carefully and I will try to make this easy.

1:Install MongoDB community version MSI from here
In the options check Install Compass, this installation can took some time so be patient.
2: Install MongoDB shell msi from here
left all the options default.
3: Install MongoDB database tools here

***Checking:***🥳

In your terminal run ' mongod --version ' Hope it's working fine.
Now run mongod to start the server although in the new update it automatically runs which you can check in the task manager.

Run ' mongosh ' which basically means mongo shell
Run in cmd run ' show dbs '

results:

2:Introduction to MongoDb:

Welcome to the world of MongoDB, where databases get a breath of fresh air! If you're tired of the same old database structures, MongoDB might just be your new best friend. In this beginner-friendly guide, we'll explore the basics of MongoDB and why it's turning heads in the tech world.

1: Bye-Bye Rigidity

Say farewell to rigid tables and fixed structures! MongoDB is all about flexibility. Instead of tables, it stores data in JSON-like documents, making it easy to adapt to changes without the headache of predefined schemas.

2: Meet the Document

Documents are the cool kids in MongoDB. Think of them as JSON objects that can hold all sorts of information. The best part? They can have different structures in the same collection. No more one-size-fits-all!

3: Collections and Databases

Organizing data is a breeze with MongoDB. Documents hang out in collections, which live in databases. It's like creating folders for your data - simple and logical.

4: Ask and You Shall Receive

Querying in MongoDB is a piece of cake. Use MongoDB Query Language (MQL) to filter, sort, and manipulate data effortlessly. No more complicated syntax – just straightforward searches!

5: Speed Boost with Indexing

Speed up your searches with MongoDB's indexing magic. Just like an index in a book, it makes finding things faster. Learn how to create and manage indexes to keep your queries running at top speed.

6: Scale Like a Pro

MongoDB knows how to grow with your app. Explore sharding, MongoDB's way of spreading data across multiple servers. It's like having your database on steroids – super strong and ready for anything.

Conclusion:

As we wrap up, remember that MongoDB brings flexibility and power to your data game. Whether you're a startup moving fast or a big player handling loads of info, MongoDB has your back. Jump in and discover the simplicity and endless possibilities waiting for you in the MongoDB universe.

3:MongoDB Atlas and Compass:

MongoDB Atlas is a fully managed cloud database service, providing an effortless way to deploy and scale MongoDB on popular cloud platforms like AWS, Azure, and Google Cloud. It offers automated backups, monitoring, and security features, allowing developers to focus on building rather than managing databases.

MongoDB Compass is the official graphical user interface (GUI) for MongoDB, offering a visual way to explore and interact with data. With an intuitive interface, Compass simplifies query building, index optimization, and data visualization, making database management more accessible for developers and administrators alike. Together, MongoDB Atlas and Compass form a dynamic duo, streamlining the development and management of MongoDB databases.

No, worries if you can't understand some terms we will discuss them letter in depth.

4: SQL Vs No-SQL

1. Data Structure:

   • SQL (Structured Query Language): SQL databases are table-based and follow a predefined schema. Data is organized into rows and columns, ensuring a structured and rigid format.

   • NoSQL (Not Only SQL): NoSQL databases, on the other hand, are more flexible. They can store data in various formats, including document-oriented (MongoDB), key-value pairs (Redis), wide-column stores (Cassandra), or graph databases (Neo4j).

2. Scalability:

   • SQL: Scaling SQL databases can be challenging, typically involving vertical scaling (upgrading hardware). While horizontal scaling is possible, it may require complex partitioning.

   • NoSQL: NoSQL databases excel at horizontal scalability. They can easily distribute data across multiple servers, making them well-suited for handling large amounts of traffic and data growth.

3. Schema:

   • SQL: Enforces a strict schema, meaning the structure of the data must be defined before inserting data. Changes to the schema can be complex and may require downtime.

   • NoSQL: Embraces a dynamic schema, allowing developers to insert data without a predefined structure. This flexibility is advantageous for evolving projects with changing data requirements.

4. Transactions:

   • SQL: ACID (Atomicity, Consistency, Isolation, Durability) transactions are a hallmark of SQL databases, ensuring reliability and consistency in data operations.

   • NoSQL: NoSQL databases often prioritize performance over strict consistency, offering eventual consistency. While some NoSQL databases support transactions, they might not provide the same level of isolation and consistency as SQL databases.

5. Use Cases:

   • SQL: Well-suited for applications with complex queries, transactions, and structured data, such as financial systems, ERP (Enterprise Resource Planning) systems, and traditional relational data.

   • NoSQL: Ideal for projects with rapidly evolving data requirements, massive amounts of data, and scenarios where horizontal scalability is crucial, like content management systems, real-time big data applications, and IoT (Internet of Things) platforms.

5: Json Vs Bson

7: Ordered and Unordered Insert Operations

You can check out remaining content in the next blog.