MongoDB Training by Experts
Our Training 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
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Course Highlights
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Instead, the documents can use the fields and structures that build the most sense for every application. It stores knowledge in document format to alter any range of records, add or delete existing fields within the table. 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. this will be possible with MongoDB, which can be as versatile because it's powerful. it's more relevant these days than ever for cloud-native applications. These operations when combined with further choices provide nice results. data sharding in MongoDB supports storing data across many machines to boost the performance of large-scale databases.
. you can experiment with database structures simply just wouldn’t be able to attain in SQL and other relative choices. MongoDB could be a collection of documents, it contains a group of key-value pairs.
