MongoDB Tutorials

MongoDB Tutorials Roadmap

Section 1: Introduction to MongoDB

  • What is MongoDB?
    • A NoSQL, document-oriented database.
    • Stores data in flexible, JSON-like documents (BSON).
    • Known for its scalability and flexibility.
  • Why MongoDB?
    • Schema flexibility.
    • High performance and scalability.
    • Rich query language.
    • Suitable for various use cases (web applications, mobile apps, content management).
  • Key Concepts:
    • Documents, Collections, Databases.
    • Differences from relational databases (tables, rows, columns).
  • Setting up MongoDB:
    • Installing MongoDB Community Edition.
    • Starting the MongoDB server.
    • Connecting to MongoDB using the MongoDB Shell (mongosh).

Section 2: Working with Data in MongoDB

  • Databases and Collections:
    • Creating and dropping databases.
    • Creating and dropping collections.
  • Inserting Documents:
    • insertOne() and insertMany().
    • Understanding the structure of a MongoDB document.
  • Querying Documents:
    • find(): Basic queries.
    • Query operators ($eq, $gt, $lt, $in, $and, $or).
    • Projections: Selecting specific fields.
    • Sorting (sort()).
    • Limiting results (limit()).
    • Skipping results (skip()).
  • Updating Documents:
    • updateOne() and updateMany().
    • Update operators ($set, $inc, $push, $pull).
  • Deleting Documents:
    • deleteOne() and deleteMany().

Section 3: Indexing and Performance

  • Understanding Indexes:
    • How indexes improve query performance.
    • Types of indexes (single-field, compound, multikey).
  • Creating and Managing Indexes:
    • createIndex().
    • getIndexes().
    • dropIndex() and dropIndexes().
  • Using explain():
    • Analyzing query execution plans.
    • Identifying performance bottlenecks.

Section 4: Aggregation Framework

  • What is the Aggregation Framework?
    • A powerful tool for data processing and analysis.
    • Processes documents in stages.
  • Common Aggregation Stages:
    • $match: Filtering documents.
    • $project: Reshaping documents.
    • $group: Grouping documents and performing calculations.
    • $sort: Sorting results.
    • $limit and $skip.
    • $lookup: Performing left outer joins (for relationships).
  • Building Aggregation Pipelines:
    • Combining multiple stages.

Section 5: Data Modeling

  • Schema Design Considerations:
    • Embedding vs. Referencing.
    • Choosing the right approach based on access patterns.
  • Modeling Different Relationships:
    • One-to-One, One-to-Many, Many-to-Many.
  • Handling Denormalization:
    • When and why to denormalize data for performance.

Section 6: Replication and Sharding

  • Replication:
    • Ensuring high availability and data redundancy.
    • Replica Sets: Primary and Secondary nodes.
    • Setting up a replica set.
    • Understanding replication concepts (oplog).
  • Sharding:
    • Scaling horizontally for large datasets and high throughput.
    • Components of a sharded cluster (Shards, Config Servers, Mongos).
    • Choosing a shard key.
    • Setting up a sharded cluster.

Section 7: Security in MongoDB

  • Authentication:
    • Enabling authentication.
    • Creating users and roles.
    • Authentication mechanisms (SCRAM-SHA-1, SCRAM-SHA-256).
  • Authorization (Role-Based Access Control):
    • Defining roles and permissions.
    • Assigning roles to users.
  • Network Security:
    • Binding to specific IP addresses.
    • Using TLS/SSL for encrypted connections.
  • Auditing (Optional):
    • Tracking database events.

Section 8: Administration and Maintenance

  • Monitoring MongoDB:
    • Using mongostat and mongotop.
    • Introduction to monitoring tools (MongoDB Cloud Manager/Ops Manager, Prometheus).
  • Backup and Restore:
    • Using mongodump and mongorestore.
    • Point-in-time recovery with replica sets.
  • Journaling:
    • Ensuring data durability.
  • Upgrading MongoDB:
    • Understanding the upgrade process.

Section 9: Working with MongoDB Drivers

  • Connecting to MongoDB from different programming languages (e.g., Node.js, Python, Java).
  • Performing CRUD operations using drivers.
  • Using the Aggregation Framework with drivers.

Section 10: Real-World Applications and Use Cases

  • Building a web application with MongoDB.
  • Using MongoDB for content management systems.
  • Examples of using MongoDB in different industries.

Section 11: Advanced Topics and Ecosystem

  • Transactions:
    • Understanding multi-document transactions in MongoDB.
  • Geospatial Queries:
    • Working with location data.
  • Text Search:
    • Performing full-text search.
  • MongoDB Atlas (Cloud Database Service):
    • Introduction to MongoDB's fully managed cloud service.
  • Learning Resources:
    • Official MongoDB documentation.
    • MongoDB University (free online courses).
    • Community blogs and forums.
    • Books and online tutorials.