MongoDB Online Live Class by Experts
Our Training/Internship Process
MongoDB - Syllabus, Fees & Duration
Module 1: Introduction to NoSQL
- What Is NoSQL?
- Why NoSQL databases are required
- Types of NoSQL Database
- NoSQL vs SQL Comparison
- ACID & BASE Property
- CAP Theorem
- Benefits of NoSQL databases
- Installation
- Start and Stop the MongoDB process
Module 2: MongoDB Architecture
- Document, Collection, Databases
- JSON and BSON
- Storage Engines
- Read Path
- Journaling
- Write Path
- Working Set
- Capped Collection
- Oplog collection
- TTL Index
- GridFS
Module 3: CRUD Operations
- MongoDB Data Types
- Inserting, Update, Deleting the documents
- Querying the documents
- Bulk insert operation
- Updating multiple document
- Limiting documents
- Filtering documents
Module 4: Schema Design and Data modeling
- Dynamic Schema
- What is Data modeling?
- RDBMS and MongoDB Data modeling difference
- Embedding Document
- Reference Document
Module 5: Indexes
- Index concepts in MongoDB
- Types of indexes
- Indexes and its use cases
- Creating Indexes
- Managing Indexes
- Index strategies
Module 6: Database Administration in MongoDB
- Database status
- Troubleshooting issues
- Current Operations
- Rotating log files
- Users and Roles
- Copy and Clone database
- DB and Collection Stats
- Explain plan
- Profiling
- Changing configuration files
- Upgrading the database
Module 7: MongoDB: Backup and Security
- Concept of backups
- mongoexport/mongoimport
- mongodump/mongorestore
- Oplog backups
- LVM Backups
- Backups using MMS/Ops Manager
- Purpose of security
- Authentication and authorization
- Role based access control
Module 8: Replication in MongoDB
- Concept of replication
- ReplicaSet member roles
- Voting and Electing primary
- Role of Oplog in replication
- Read and Write Concern
- Arbiter,Hidden and Delayed replica node
- Priority settings
- Replicaset nodes health check
- Concept of resyncing the nodes
- Rollbacks during failover
- Keyfile authentication
Module 9: MongoDB Scalability
- Concept of Scalability
- Sharding concept
- Shardkey and Chunks
- Choosing shardkey
- Sharding components
- Types of Sharding
- Balanced data distribution
- Sharded and Non-sharded collection
- Sharded Replicaset
- Tag aware sharding
Module 10: MongoDB Monitoring and Other Tools
- MMS Manager
- Ops Manager
- Mongo utility commands
- Mongo developer tools
- MongoDB Atlas
- MongoDB client drivers
This syllabus is not final and can be customized as per needs/updates
- Since 2001, Making IT Experts by Experts
- Duration: 90 Hours (Vary as per your skill)
- Course Fees
- Individual Live Classes (1:1)
- Batch Classes @ Low Fees
- Training on Your Time, Any Where
- Access to Recorded Videos
- Practical Internship on Projects
- 100% Placement Support by our jobsNEAR.in
- Training/Internship Certificate
- Abbotsford
- Alberta
- Barrie
- Brampton
- British Columbia
- Burlington
- Calgary
- Charlottetown
- Delta
- Edmonton
- Gatineau
- Guelph
- Halifax
- Hamilton
- Kamloops
- Kelowna
- Kingston
- Kitchener
- Manitoba
- Mississauga
- Moncton
- Montreal
- Nanaimo
- New Brunswick
- Niagara Falls
- Nova Scotia
- Ontario
- Oshawa
- Ottawa
- Peterborough
- Prince George
- Quebec
- Regina
- Saint John
- Saskatoon
- Sherbrooke
- Surrey
- Thunder Bay
- Toronto
- Vancouver
- Victoria
- Waterloo
- Whitehorse
- Windsor
- Winnipeg
Course Highlights
Our Locations
the most effective MongoDB online training Institute. Any organization has this database to store dynamic data in the cloud and on-premises environments. Complete, updated list.
. we teach you how to unleash the facility of MongoDB in incorporating data, performing real-time analytics, managing content, other functions. data sharding in MongoDB supports storing data across many machines to boost the performance of large-scale databases. Relative databases have rigid schemes that limit flexibility with the data structure. you can experiment with database structures simply just wouldn’t be able to attain in SQL and other relative choices. MongoDB works with wealthy JSON Documents, supports a robust query language, Supports aggregations and different trendy use-cases similar to geo-based search, graph search, and text search. the two situations that it addresses specifically are indexes that don’t work into memory and write-heavy data. 
