MongoDB Training by Experts

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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

Download Syllabus - MongoDB
This syllabus is not final and can be customized as per needs/updates
 
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MongoDB Jobs in Austin

Enjoy the demand

Find jobs related to MongoDB in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Austin, chennai and europe countries. You can find many jobs for freshers related to the job positions in Austin.

  • Full Stack Developer
  • Databases Specialist
  • Database Admin
  • Consulting Engineer
  • Database Engineer
  • MongoDB Engineer
  • Database Administrator
  • Technology Engineer
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  • MongoDB Trainer

MongoDB Internship/Course Details

MongoDB internship jobs in Austin
MongoDB Complete, updated list. Learn the most effective skills from the best sources through the best trustworthy academics. the two situations that it addresses specifically are indexes that don’t work into memory and write-heavy data. it will store complicated structures easily, fetch the info more accurately. Complete, updated list. built-in scaling may be a must-have feature of many organizations, as you adapt to an ever-changing market. 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. data sharding in MongoDB supports storing data across many machines to boost the performance of large-scale databases. data is unbroken as a document using tables and rows as in a relational database.

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