Comprehensive MongoDB: From Basics to Advanced

What is MongoDB and why it is used?

MongoDB is built on a scale-out architecture that has become popular with developers of all kinds for developing scalable applications with evolving data schemas. As a document database, MongoDB makes it easy for developers to store structured or unstructured data. It uses a JSON-like format to store documents.

Is MongoDB good for beginners?

MongoDB is a NoSQL (non-relational) database. There are several types of NoSQL databases, and MongoDB is a document-based NoSQL database that is open source. This MongoDB lesson is meant for beginners, so even if you have no prior understanding of the database, you will be able to grasp it.

What skills are required for MongoDB?

For MongoDB, you need to have an understanding of databases first. How they work, SQL – NOSQL, Not deep knowledge just basic understanding of how a database works. Then you can start learning MongoDB. TalhaTraining has courses on talhatraining.com for basics as well as advanced learning.

The benefit of learning MongoDB.

Learning MongoDB can be highly beneficial for developers and organizations working with modern, dynamic data-driven applications that require scalability, flexibility, and high performance. It’s particularly well-suited for projects involving big data, real-time analytics, content management systems, and many other applications.

Module 1: Introduction to MongoDB and NoSQL Databases

• Understanding the role of databases in applications
• Introduction to NoSQL databases and MongoDB
• Comparing relational databases and NoSQL databases
• Installing and setting up MongoDB

Module 2: Basics of Data Modeling in MongoDB

• Document-oriented data model in MongoDB
• BSON format and data types
• Creating and inserting documents
• Retrieving documents using find()

Module 3: Querying and Projection

• Querying documents using operators (comparison, logical, etc.)
• Projection: selecting specific fields from documents
• Sorting and limiting results
• Indexing for faster queries

Module 4: Data Manipulation and Aggregation Framework

• Updating documents using update() and updateOne()
• Deleting documents using delete() and deleteOne()
• Introduction to the Aggregation Framework
• Aggregation stages: match, project, group, sort, etc.

Module 5: Advanced Querying and Indexing

• Query optimization and using explain()
• Text search and full-text indexing
• Geospatial queries and indexing
• Compound indexes and optimizing queries

Module 6: Data Modeling: Relationships and Embedding

• Modeling relationships using references
• Denormalization and embedding documents
• One-to-one, one-to-many, and many-to-many relationships
• Pros and cons of different data modeling approaches

Module 7: Working with Geospatial Data

• Storing and querying geospatial data
• Using 2D and 2D sphere indexes for geospatial queries
• Calculating distances and finding nearby locations

Module 8: Aggregation Pipeline and Data Transformation

• Advanced usage of the Aggregation Framework
• Combining multiple stages in the aggregation pipeline
• Projecting, transforming, and reshaping data
• Building complex queries using the pipeline

Module 9: Transactions and Data Consistency

• Understanding transactions and their importance
• Implementing multi-document transactions
• Ensuring data consistency and atomicity

Module 10: MongoDB Atlas and Cloud Deployment

• Introduction to MongoDB Atlas, the cloud database service
• Setting up a MongoDB Atlas cluster
• Migrating data to the cloud
• Benefits and considerations of using cloud-based databases

Module 11: Security and Authentication

• User authentication and roles in MongoDB
• Role-based access control (RBAC)
• Security best practices and considerations

Module 12: Scaling and Sharding

• Understanding horizontal scaling and sharding
• Implementing sharding in MongoDB
• Balancing data across shards
• Strategies for scaling MongoDB databases

Module 13: Advanced Topics and Trends

• Exploring the MongoDB Atlas Data Lake
• Introduction to MongoDB Realm for serverless application development
• Exploring MongoDB’s support for time-series data
• Emerging trends in the MongoDB ecosystem

Module 14: Final Project and Recap

• Students work on a final project applying the knowledge gained
• Presenting and reviewing the final projects
• Recap of key concepts covered in the course