Download to read offline
![Types of No SQl data base
Key Value pair
Dynamo DB
Azure Table Storage (ATS )
Graph database
Document Based
Mango Db
AmazonSimple DB
Couch DB
Column Oriented database
(#key,#value)
(Name, Tom)
(Age,25)
(Role, Student)
(University, CU)
[
{
"Name": "Tom",
"Age": 30,
"Role": "Student",
"University":
"CU",
}
]
Student
Tom
CU
25
Masters
Ottawa Location
• Neo4j
• Infogrid
Row Id Columns
1
Name Tom
Age 25
Role Student
Bigtable(Google)
HBase](https://image.slidesharecdn.com/mongodb-200101050335/85/Mongodb-Introduction-4-320.jpg)
![Document(JSON) structure
The document has simple structure and very easy to
understand the content
JSON is smaller, faster and lightweight compared to XML.
For data delivery between servers and browsers, JSON is a
better choice
Easy in parsing, processing, validating in all languages
JSON can be mapped more easily into object oriented
system.
[
{
"Name": "Tom",
"Age": 30,
"Role": "Student",
"University": "CU",
}
{
"Name": “Sam",
"Age": 32,
"Role": "Student",
"University": “OU",
}
]](https://image.slidesharecdn.com/mongodb-200101050335/85/Mongodb-Introduction-12-320.jpg)
![Types of No SQl data base
Key Value pair
Dynamo DB
Azure Table Storage (ATS )
Graph database
Document Based
Mango Db
AmazonSimple DB
Couch DB
Column Oriented database
(#key,#value)
(Name, Tom)
(Age,25)
(Role, Student)
(University, CU)
[
{
"Name": "Tom",
"Age": 30,
"Role": "Student",
"University":
"CU",
}
]
Student
Tom
CU
25
Masters
Ottawa Location
• Neo4j
• Infogrid
Row Id Columns
1
Name Tom
Age 25
Role Student
Bigtable(Google)
HBase](https://image.slidesharecdn.com/mongodb-200101050335/75/Mongodb-Introduction-4-2048.jpg)
![Document(JSON) structure
The document has simple structure and very easy to
understand the content
JSON is smaller, faster and lightweight compared to XML.
For data delivery between servers and browsers, JSON is a
better choice
Easy in parsing, processing, validating in all languages
JSON can be mapped more easily into object oriented
system.
[
{
"Name": "Tom",
"Age": 30,
"Role": "Student",
"University": "CU",
}
{
"Name": “Sam",
"Age": 32,
"Role": "Student",
"University": “OU",
}
]](https://image.slidesharecdn.com/mongodb-200101050335/75/Mongodb-Introduction-12-2048.jpg)
Uploaded byNabeel Naqeebi
Mongodb Introduction
This document provides an introduction to MongoDB, a NoSQL database, discussing its architecture, key features, advantages over traditional RDBMS, and limitations. It outlines the different types of NoSQL databases, highlights MongoDB's document-oriented structure using JSON, and describes the setup process and common operations. The document emphasizes MongoDB's scalability and flexibility, making it suitable for modern applications dealing with large volumes of unstructured data.
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Mongodb Introduction
- 1. Introduction to MongoDB (NO SQL data Base) PREPARED BY: NABEEL RAZA
- 2. Overview What isNO SQL Data base? Types of NO SQL Data base. What is Mongo DB? RDBMs vs MongoDB Why Mongo DB? Limitation of MongoDB Mongo DB Architecture. Document (JSON) Structure. MongoDB environment setup Different Methods. Demo When to use Mongo DB?
- 3. What is NoSQL data base It’s Not No SQL it’s NOT ONLY SQL. NoSQL is a non-relational DBMS, that does not require a fixed schema, avoids joins, and is easy to scale. It’s not even a replacement to RDBMS. NoSQL databases are increasingly used in big data and real-time web applications. For example, companies like Twitter, Facebook, Google that collect terabytes of user data every single day.
- 4. Types of NoSQl data base Key Value pair Dynamo DB Azure Table Storage (ATS ) Graph database Document Based Mango Db AmazonSimple DB Couch DB Column Oriented database (#key,#value) (Name, Tom) (Age,25) (Role, Student) (University, CU) [ { "Name": "Tom", "Age": 30, "Role": "Student", "University": "CU", } ] Student Tom CU 25 Masters Ottawa Location • Neo4j • Infogrid Row Id Columns 1 Name Tom Age 25 Role Student Bigtable(Google) HBase
- 5. What is MongoDB MongoDB is a cross-platform, document oriented database that provides High performance. High availability. Easy scalability. MongoDB uses JSON-like documents with schema. MongoDB works on concept of collection and document. Developed by: MongoDB Inc.
- 6.
- 7. Why Mongo DB? All the modern applications deals with huge data. Development with ease is possible with mongo DB. Flexibility in deployment. Older database systems may not be compatible with the design. And it’s a document oriented storage:- Data is stored in the form of JSON Style.
- 8. Who are UsingMongoDB? A survey by Siftery on MongoDB, there are around 4000+ company confirmed that they are using MongoDB as Database. Some of the key names are : • Castlight Health • IBM • Citrix • Twitter • T-Mobile • Zendesk • Sony • BrightRoll • Foursquare • HTC • InVision • Intercom etc.
- 9. Limitation of MongoDB Nothing is fully complete or perfect. Joins not Supported( Joins functionality by adding by coding it manually) High Memory Usage. Limited Data Size(document size, not more than 16MB.) Limited Nesting(cannot perform nesting of documents for more than 100 levels.)
- 10.
- 11. Mongo DB architecture Architecture: - Database ContainerDocument
- 12. Document(JSON) structure Thedocument has simple structure and very easy to understand the content JSON is smaller, faster and lightweight compared to XML. For data delivery between servers and browsers, JSON is a better choice Easy in parsing, processing, validating in all languages JSON can be mapped more easily into object oriented system. [ { "Name": "Tom", "Age": 30, "Role": "Student", "University": "CU", } { "Name": “Sam", "Age": 32, "Role": "Student", "University": “OU", } ]
- 13. Difference Between XMLAnd JSON XML JSON It is a markup language. It is a way of representing objects. This is more verbose than JSON. This format uses less words. It is used to describe the structured data. It is used to describe unstructured data which include arrays. Example: <car> <company>Volkswagen</company> <name>Vento</name> <price>800000</price> </car> { "company": Volkswagen, "name": "Vento", "price": 800000 }
- 14. MongoDB Environment Setup Know your Windows architecture Download MongoDB setup file Install MongoDB setup Set up MongoDB Environment Connect to the MongoDB server MongoDB as a Windows service Create configuration file Run MongoDB Environment setup
- 15. Know your WindowsArchitecture You must know which Windows version you are using. To know about your system architecture, open the command prompt and execute some commands given below. Command: wmic os get osarchitecture. Download the MongoDB setup accordingly.
- 16. Download MongoDB SetupFile Download the latest version of MongoDB from the official website. Link: ttps://www.mongodb.org/downloads Download the MSI file from this server. And install mongodb setup. There is an option to install MongoDB Compass too.
- 17. MongoDB Environment Setup MongoDB stored data in a specified directory. Create it manually in the MongoDB Folder on the C drive. Run the command in Command Prompt.(md datadb)
- 18. Start MongoDB Tostart mongodb server, we need to run the specific file.
- 19.
- 20. Connect to MongoDBServer After executing the MongoDB.exe file, Now we need to connect it to the MongoDB server. We will connect it through Mongo.exe shell by opening another command prompt.
- 21. MongoDB as aWindows Service Create some directories using command prompt & executing the following commands: mkdir c:datadb mkdir c:datalog All of your database and the log files will be stored in these two folders.
- 22. MongoDB Document Structure There are TWO types of documents Referenced Documents Embedded Documents
- 23. Referenced Document Storethe relationship between data by including links from one data to another.
- 24. Embedded Documents Embeddeddocuments create relationships between data by storing related data in a single document structure.
- 25.
- 26.
- 27. Some commonly used Commands Use Command: to use the database. DB Command: to check selected DB Show dbs: list all databases dropDatabase: to drop selected db Example: - • Use database_name; • Db; • Show dbs; • dropDatabase()
- 28. The createCollection() Method Firstwe create database As we know there are table(s) in a database And tables are know as documents First create Collection using command “db. createCollection(name,option)” Example: - Db.createCollection(“myTable”)
- 29. The insert() Method To insert data into MongoDB collection, you need to use MongoDB's insert() or save() method. The basic syntax of insert() command is as follows − “db.COLLECTION_NAME.insert(document)” Example: - db.StudentRecord.insert ( { "Name": "Tom", "Age": 30, "Role": "Student", "University": "CU", }, { "Name": “Sam", "Age": 22, "Role": "Student", "University": “OU", } )
- 30. The find() Method To query data from MongoDB collection, you need to use MongoDB's find() method. The basic syntax of find() method is as follows − “db.COLLECTION_NAME.find()” find() method will display all the documents in a non-structured way. To display the results in a formatted way, you can use pretty() method. “db.mycol.find().pretty() “ Example: - db.StudentRecord.find() .pretty()
- 31. The update() Method As we know that database consists of some Collection and each collection have some documents. Update this document by adding some more information. “db.collection_name.update(criteria, update_data )” db.studentRecord.update( { "Name":"Tom", "Age":30}, { $set: { "Name":"Tommy“, "Age":35 } } } )
- 32. The remove() Method MongoDB's remove() method is used to remove a document from the collection. remove() method accepts two parameters. One is deletion criteria and second is justOne flag. deletion criteria − (Optional) deletion criteria according to documents will be removed. justOne − (Optional) if set to true or 1, then remove only one document. Syntax db.COLLECTION_NAME.remove(DELLETI ON_CRITTERIA) Remove based on DELETION_CRITERIA db.StudentRecord.remove({"Name": "Tommy}) Remove Only One:-Removes first record db.StudentRecord.remove(DELETION _CRITERIA,1) Remove all Records db.StudentRecord.remove()
- 33. When to useMongo Db? When your requirements has these properties : You absolutely must store unstructured data. Things coming from 3rd-party API you don’t control. Logs whose format may change any minute. You change your schema very often on a large dataset.
Editor's Notes
- #6 Ad-hoc Queries Schema-Less Database Document-Oriented Indexing Replication Aggregation GridFS Sharding High Performance
- #8 Flexible database – Sharding(1-3) - High Speed - Ad-hoc Query Support -
- #10 Joins: But it may slow execution and affect performance. Memory: due to no functionality of joins, there is data redundancy. This results in increasing unnecessary usage of memory.
- #17 MongoDB Compass is the GUI for MongoDB. Compass allows you to analyze and understand the contents of your data without formal knowledge of MongoDB query syntax.
- #29 >db.createCollection(“mongodb”, { capped:true, size:1000000, max:2})