The document discusses connecting Node.js applications to NoSQL MongoDB databases using Mongoose. It begins with an introduction to MongoDB and NoSQL databases. It then covers how to install Mongoose and connect a Node.js application to a MongoDB database. It provides examples of performing CRUD operations in MongoDB using Mongoose, including inserting, updating, and deleting documents.
This document provides an introduction and overview of MongoDB. It begins with defining what a database and NoSQL database are. MongoDB is introduced as a popular open-source document-oriented NoSQL database that stores data in BSON documents. The document outlines some key advantages of MongoDB like its flexibility and support for many programming languages. It then covers how to set up a local MongoDB server, perform basic CRUD operations, and query documents. Finally, it introduces MongoDB Atlas as a cloud database service that handles deploying and managing MongoDB in the cloud.
MongoDB is a popular open-source NoSQL database that uses a document-oriented data model. It provides high performance, high availability, and easy scalability by eliminating the need for an ORM. Mongoose allows defining schemas and models for MongoDB collections and provides features like validation, middleware support, and CRUD operations when connecting MongoDB with Node.js applications.
This document contains information about Justin Smestad and MongoDB. It includes Justin's contact information and background working as a software engineer with skills in Ruby, JavaScript, Clojure, and passion for DevOps. It also provides an overview of MongoDB, describing it as a scalable, high-performance, open source, schema-free, document-oriented database. Key features of MongoDB like indexing, master-slave replication, and horizontal scaling with replica sets and sharding are summarized.
Introduction to MongoDB Basics from SQL to NoSQLMayur Patil
This document provides an introduction to databases and MongoDB. It discusses the purpose of databases, types of databases including relational and non-relational, and the relational model. It then focuses on MongoDB, describing its basics like JSON and BSON storage formats, CRUD terms, features around performance, availability and scaling, and some limitations. Popular applications of databases are also listed.
MongoDB is a document-oriented NoSQL database that provides polyglot persistence and multi-model capabilities. It supports document, graph, relational, and key-value data models through a single backend. MongoDB also provides tunable consistency levels, secondary indexing, aggregation capabilities, and multi-document ACID transactions. Mature drivers simplify application development, while MongoDB Atlas provides a fully managed cloud database service with high availability, security, and monitoring.
MongoDB is a document database that stores data in BSON format, which is similar to JSON. It is a non-relational, schema-free database that scales easily and supports massive amounts of data and high availability. MongoDB can replace traditional relational databases for certain applications, as it offers dynamic schemas, horizontal scaling, and high performance. Key features include indexing, replication, MapReduce and rich querying of embedded documents.
3-Mongodb and Mapreduce Programming.pdfMarianJRuben
The document discusses MongoDB and MapReduce. It provides an introduction to MongoDB and NoSQL databases. It then explains the MapReduce programming paradigm in MongoDB, which allows processing large datasets and producing aggregated results. It describes the map and reduce functions used in MapReduce and provides an example of a simple MapReduce operation to count the number of visits to different web pages from log data.
MongoDB is a scalable, high-performance, open-source NoSQL database that stores data in flexible, JSON-like documents. It is used by organizations of all sizes for applications where low latency and high availability are important. MongoDB is document-based, schemaless, and supports high performance, horizontal scalability through sharding and replication.
This presentation is related to nosql database and nosql database types information. this presentationa also contains discussion about, how mongodb works and mongodb security and mongodb sharding information.
This document provides an introduction to MongoDB, a non-relational NoSQL database. It discusses what NoSQL databases are and their benefits compared to SQL databases, such as being more scalable and able to handle large, changing datasets. It then describes key features of MongoDB like high performance, rich querying, and horizontal scalability. The document outlines concepts like document structure, collections, and CRUD operations in MongoDB. It also covers topics such as replication, sharding, and installing MongoDB.
MongoDB is a popular open-source document-oriented NoSQL database that uses a document-based data model. It stores data in flexible, JSON-like documents, allowing for easy storage and retrieval of data without rigid schemas. MongoDB is horizontally scalable, supports replication and high availability, and is often used for applications that require more flexibility than relational databases or have very large amounts of data.
MongoDB is a horizontally scalable, schema-free, document-oriented NoSQL database. It stores data in flexible, JSON-like documents, allowing for easy storage and retrieval of data without rigid schemas. MongoDB provides high performance, high availability, and easy scalability. Some key features include embedded documents and arrays to reduce joins, dynamic schemas, replication and failover for availability, and auto-sharding for horizontal scalability.
The document describes the basics of MongoDB, including that it uses databases containing collections which are made up of documents with fields. Collections can be indexed to improve performance of lookups and sorting. When data is retrieved from MongoDB, it is through a cursor which delays execution until needed. While similar concepts exist in relational databases, MongoDB's documents can have unique fields compared to tables with predefined columns.
This document provides information about MongoDB, including:
- MongoDB is a non-SQL database that stores data as flexible documents rather than rows and tables. It is suitable for large, unstructured datasets.
- Key features include document-oriented storage, full indexing support, replication for high availability, auto-sharding for scalability, and querying capabilities.
- CRUD operations like insert, find, update, and delete can be performed on MongoDB collections and documents using methods like db.collection.insert() and db.collection.find(). Aggregation operations allow computing results by processing documents.
The document discusses NoSQL databases and MongoDB. It defines NoSQL, describes different types of NoSQL databases like key-value, document, graph and column-oriented. It then focuses on MongoDB, explaining its advantages like high performance, flexibility and rich queries. It covers MongoDB concepts like collections and documents. It also discusses JSON structure, MongoDB methods for insertion, querying and removal of documents. Finally, it provides examples of when to use MongoDB, such as for unstructured data, high volume read/writes and changing schemas.
This document provides an introduction to MongoDB and Python. It discusses how to install and run MongoDB, set up a Python environment connected to MongoDB, perform basic read and write operations on MongoDB collections from Python. It also covers common patterns for modeling data in MongoDB like embedding documents and indexing, and integrating MongoDB with popular Python web frameworks.
Basic of Mongodb With the description of NoSQl database and its features about colleactions and documents.Its advantages and disadvantages.Why to use MongoDB.Difference between RDBMS and MongoDB.Installation process of MongoDB.Varoius BSON Types.Keypoints Of MongoDB.
Keywords:NOSQL,BSON Types,Replication,Sharding,Aggregations,ObjectId and various others.
1> Why Choose NoSQL
2> MongoDB -NoSQL Database
3> MongoDB BioGraphy
4> RDBMS VS MongoDB
5> Query Language in MYSQL Vs MongoDB
6> Key Features
7> MongoDB Basics
8> MongoDB Collections
9> MongoDB Aggregations
10> Aggregation Pipeline
11> Single Purpose Aggregation Operations
12> MongoDB Replication
13> Sharding in MongoDB
14> Pros / Cons Of MongoDB
15> Why should use MongoDB
17> Where should use MongoDB?
Conclusion:MongoDB database is used to store big data.It gives high performance and scalability features which makes advanced in terms of SQL database
This document provides an overview and introduction to NoSQL databases, focusing on MongoDB. It begins with definitions of NoSQL and examples of companies using NoSQL databases. It then discusses the motivations behind NoSQL, including the limitations of SQL and benefits of NoSQL for scalability. The document proceeds to describe MongoDB specifically as a document-oriented database, covering its data model, networking, drivers, collections and indexing. It also covers queries, atomic operations, replication, sharding, map-reduce and GridFS for large files. Well suited use cases include archiving, content management, ecommerce, gaming and mobile applications. The document concludes with a question and contact.
The document provides information about The Little MongoDB Book by Karl Seguin. It discusses the book's license, which allows copying and distributing the book non-commercially while attributing the author. It introduces the author Karl Seguin and his experience and other works. It thanks Perry Neal for assistance and notes the latest version was updated by Asya Kamsky.
MongoDB NoSQL database a deep dive -MyWhitePaperRajesh Kumar
This document provides an overview of MongoDB, a popular NoSQL database. It discusses why NoSQL databases were created, the different types of NoSQL databases, and focuses on MongoDB. MongoDB is a document-oriented database that stores data in JSON-like documents with dynamic schemas. It provides horizontal scaling, high performance, and flexible data models. The presentation covers MongoDB concepts like databases, collections, documents, CRUD operations, indexing, sharding, replication, and use cases. It provides examples of modeling data in MongoDB and considerations for data and schema design.
This document provides an overview of NoSQL databases and MongoDB. It states that NoSQL databases are more scalable and flexible than relational databases. MongoDB is described as a cross-platform, document-oriented database that provides high performance, high availability, and easy scalability. MongoDB uses collections and documents to store data in a flexible, JSON-like format.
MongoDB is an open-source document database, and the leading NoSQL database. Written in C++.
MongoDB has official drivers for a variety of popular programming languages and development environments. There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.
This document provides information about The Little MongoDB Book. It states that the book is licensed under a Creative Commons license that allows copying and distributing the book non-commercially as long as the author is attributed. It introduces the author Karl Seguin and his experience and credentials. It thanks Perry Neal for his help with the book. It provides the location of the latest version of the book source code online.
MongoDB is a document-oriented NoSQL database that stores data in flexible JSON-like documents. It does not enforce a schema on collections of documents and allows embedding related data. Key features include dynamic schemas, indexing, replication for high availability, and horizontal scaling through sharding of data across machines. Documents are organized into collections, databases are containers for collections, and the basic components include the _id field, collections, cursors, databases, documents, fields, and storage of data in JSON format.
The document discusses the evolution of databases from flat files to relational databases to NoSQL databases like MongoDB. It provides an overview of MongoDB, describing it as a free, open-source, cross-platform, document-oriented database designed for scalability. Some key features of MongoDB are that it uses dynamic schemas, is horizontally scalable, and supports replication and sharding for high availability. The document also compares MongoDB to relational databases and provides examples of CRUD operations and data modeling in MongoDB.
Generative AI refers to a subset of artificial intelligence that focuses on creating new content, such as images, text, music, and even videos, based on the data it has been trained on. Generative AI models learn patterns from large datasets and use these patterns to generate new content.
Microsoft Power BI is a business analytics service that allows users to visualize data and share insights across an organization, or embed them in apps or websites, offering a consolidated view of data from both on-premises and cloud sources
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The document discusses MongoDB and MapReduce. It provides an introduction to MongoDB and NoSQL databases. It then explains the MapReduce programming paradigm in MongoDB, which allows processing large datasets and producing aggregated results. It describes the map and reduce functions used in MapReduce and provides an example of a simple MapReduce operation to count the number of visits to different web pages from log data.
MongoDB is a scalable, high-performance, open-source NoSQL database that stores data in flexible, JSON-like documents. It is used by organizations of all sizes for applications where low latency and high availability are important. MongoDB is document-based, schemaless, and supports high performance, horizontal scalability through sharding and replication.
This presentation is related to nosql database and nosql database types information. this presentationa also contains discussion about, how mongodb works and mongodb security and mongodb sharding information.
This document provides an introduction to MongoDB, a non-relational NoSQL database. It discusses what NoSQL databases are and their benefits compared to SQL databases, such as being more scalable and able to handle large, changing datasets. It then describes key features of MongoDB like high performance, rich querying, and horizontal scalability. The document outlines concepts like document structure, collections, and CRUD operations in MongoDB. It also covers topics such as replication, sharding, and installing MongoDB.
MongoDB is a popular open-source document-oriented NoSQL database that uses a document-based data model. It stores data in flexible, JSON-like documents, allowing for easy storage and retrieval of data without rigid schemas. MongoDB is horizontally scalable, supports replication and high availability, and is often used for applications that require more flexibility than relational databases or have very large amounts of data.
MongoDB is a horizontally scalable, schema-free, document-oriented NoSQL database. It stores data in flexible, JSON-like documents, allowing for easy storage and retrieval of data without rigid schemas. MongoDB provides high performance, high availability, and easy scalability. Some key features include embedded documents and arrays to reduce joins, dynamic schemas, replication and failover for availability, and auto-sharding for horizontal scalability.
The document describes the basics of MongoDB, including that it uses databases containing collections which are made up of documents with fields. Collections can be indexed to improve performance of lookups and sorting. When data is retrieved from MongoDB, it is through a cursor which delays execution until needed. While similar concepts exist in relational databases, MongoDB's documents can have unique fields compared to tables with predefined columns.
This document provides information about MongoDB, including:
- MongoDB is a non-SQL database that stores data as flexible documents rather than rows and tables. It is suitable for large, unstructured datasets.
- Key features include document-oriented storage, full indexing support, replication for high availability, auto-sharding for scalability, and querying capabilities.
- CRUD operations like insert, find, update, and delete can be performed on MongoDB collections and documents using methods like db.collection.insert() and db.collection.find(). Aggregation operations allow computing results by processing documents.
The document discusses NoSQL databases and MongoDB. It defines NoSQL, describes different types of NoSQL databases like key-value, document, graph and column-oriented. It then focuses on MongoDB, explaining its advantages like high performance, flexibility and rich queries. It covers MongoDB concepts like collections and documents. It also discusses JSON structure, MongoDB methods for insertion, querying and removal of documents. Finally, it provides examples of when to use MongoDB, such as for unstructured data, high volume read/writes and changing schemas.
This document provides an introduction to MongoDB and Python. It discusses how to install and run MongoDB, set up a Python environment connected to MongoDB, perform basic read and write operations on MongoDB collections from Python. It also covers common patterns for modeling data in MongoDB like embedding documents and indexing, and integrating MongoDB with popular Python web frameworks.
Basic of Mongodb With the description of NoSQl database and its features about colleactions and documents.Its advantages and disadvantages.Why to use MongoDB.Difference between RDBMS and MongoDB.Installation process of MongoDB.Varoius BSON Types.Keypoints Of MongoDB.
Keywords:NOSQL,BSON Types,Replication,Sharding,Aggregations,ObjectId and various others.
1> Why Choose NoSQL
2> MongoDB -NoSQL Database
3> MongoDB BioGraphy
4> RDBMS VS MongoDB
5> Query Language in MYSQL Vs MongoDB
6> Key Features
7> MongoDB Basics
8> MongoDB Collections
9> MongoDB Aggregations
10> Aggregation Pipeline
11> Single Purpose Aggregation Operations
12> MongoDB Replication
13> Sharding in MongoDB
14> Pros / Cons Of MongoDB
15> Why should use MongoDB
17> Where should use MongoDB?
Conclusion:MongoDB database is used to store big data.It gives high performance and scalability features which makes advanced in terms of SQL database
This document provides an overview and introduction to NoSQL databases, focusing on MongoDB. It begins with definitions of NoSQL and examples of companies using NoSQL databases. It then discusses the motivations behind NoSQL, including the limitations of SQL and benefits of NoSQL for scalability. The document proceeds to describe MongoDB specifically as a document-oriented database, covering its data model, networking, drivers, collections and indexing. It also covers queries, atomic operations, replication, sharding, map-reduce and GridFS for large files. Well suited use cases include archiving, content management, ecommerce, gaming and mobile applications. The document concludes with a question and contact.
The document provides information about The Little MongoDB Book by Karl Seguin. It discusses the book's license, which allows copying and distributing the book non-commercially while attributing the author. It introduces the author Karl Seguin and his experience and other works. It thanks Perry Neal for assistance and notes the latest version was updated by Asya Kamsky.
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This document provides an overview of MongoDB, a popular NoSQL database. It discusses why NoSQL databases were created, the different types of NoSQL databases, and focuses on MongoDB. MongoDB is a document-oriented database that stores data in JSON-like documents with dynamic schemas. It provides horizontal scaling, high performance, and flexible data models. The presentation covers MongoDB concepts like databases, collections, documents, CRUD operations, indexing, sharding, replication, and use cases. It provides examples of modeling data in MongoDB and considerations for data and schema design.
This document provides an overview of NoSQL databases and MongoDB. It states that NoSQL databases are more scalable and flexible than relational databases. MongoDB is described as a cross-platform, document-oriented database that provides high performance, high availability, and easy scalability. MongoDB uses collections and documents to store data in a flexible, JSON-like format.
MongoDB is an open-source document database, and the leading NoSQL database. Written in C++.
MongoDB has official drivers for a variety of popular programming languages and development environments. There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.
This document provides information about The Little MongoDB Book. It states that the book is licensed under a Creative Commons license that allows copying and distributing the book non-commercially as long as the author is attributed. It introduces the author Karl Seguin and his experience and credentials. It thanks Perry Neal for his help with the book. It provides the location of the latest version of the book source code online.
MongoDB is a document-oriented NoSQL database that stores data in flexible JSON-like documents. It does not enforce a schema on collections of documents and allows embedding related data. Key features include dynamic schemas, indexing, replication for high availability, and horizontal scaling through sharding of data across machines. Documents are organized into collections, databases are containers for collections, and the basic components include the _id field, collections, cursors, databases, documents, fields, and storage of data in JSON format.
The document discusses the evolution of databases from flat files to relational databases to NoSQL databases like MongoDB. It provides an overview of MongoDB, describing it as a free, open-source, cross-platform, document-oriented database designed for scalability. Some key features of MongoDB are that it uses dynamic schemas, is horizontally scalable, and supports replication and sharding for high availability. The document also compares MongoDB to relational databases and provides examples of CRUD operations and data modeling in MongoDB.
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Microsoft Power BI is a business analytics service that allows users to visualize data and share insights across an organization, or embed them in apps or websites, offering a consolidated view of data from both on-premises and cloud sources
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4. 1. Centralised Database
• The information(data) is stored at a centralized location and
the users from different locations can access this data.
• This type of database contains application procedures that
help the users to access the data even from a remote
location.
5. Distributed Database
•Just opposite of the centralized database concept,
•The data is not at one place and is distributed at various
sites of an organization. These sites are connected to
each other with the help of communication links which
helps them to access the distributed data easily.
6. Introduction to NoSQL
•NoSQL is a type of database management
system (DBMS) that is designed to handle and
store large volumes of unstructured and semi-
structured data.
•NoSQL originally referred to “non-SQL” or “non-
relational” databases
7. NoSQL Database
•It is used for large sets of distributed data.
•There are some big data performance issues which are
effectively handled by relational databases, such kind of
issues are easily managed by NoSQL databases.
•There are very efficient in analyzing large size unstructured
data that may be stored at multiple virtual servers of the
cloud.
8. Cloud and Database
• A cloud is a network of remote servers that are connected to the
internet, and are used to store, manage and process data.
• Cloud services can be divided into three categories:
• Infrastructure as a Service (IaaS),
• Platform as a Service (PaaS) and
• Software as a Service (SaaS). T
• he main benefit of cloud computing is its scalability, as well as its
ability to provide on-demand access to computing resources and
services.
9. Cloud and Database
• A database is a collection of data that is organized in a specific way
and can be accessed, managed and updated by a software
application.
• Databases are used to store and retrieve data in an efficient and
organized manner.
• There are different types of databases, such as
• relational databases (MySQL, Oracle, MS SQL), NoSQL databases
(MongoDB, Cassandra, Redis) and graph databases (Neo4j).
10. Cloud and Database
•cloud is a type of technology that provides access to
remote servers and computing resources
•database is a collection of data that is organized and
managed by a specific software.
•While they are different, they can be used together,
such as running a database in a cloud environment.
12. JSON / JavaScript Object Notation Basics
• It is a text-based data exchange format.
• It is a collection of key-value pairs
• where the key must be a string type, and the value can be of any of the
following types:
• Number
• String
• Boolean
• Array
• Object
• null
18. MongoDB
• MongoDB is a NoSQL database.
• MongoDB is an open source, document oriented database
that stores data in form of documents (key and value pairs).
19. Fields (key and value pairs) are stored in document, documents are
stored in collection and collections are stored in database.
21. CRUD operations in MongoDB
• Create: This operation allows you to insert new documents into a
MongoDB collection. A document is a data structure that consists of field-
value pairs, similar to a JSON object.
• Read: This operation allows you to retrieve data from a MongoDB
collection. You can retrieve a single document or multiple documents that
match a specific query.
• Update: This operation allows you to modify existing documents in a
MongoDB collection. You can update one or multiple documents that
match a specific query.
• Delete: This operation allows you to remove documents from a MongoDB
collection. You can delete a single document or multiple documents that
match a specific query.
22. Download MongoDB
•download MongoDB from the official website:
https://www.mongodb.com/download-center/communi
ty
.
• MongoDB driver for our programming language.
•using the official MongoDB driver for Node.js.
•You can install it by running the following command:
npm install mongodb
npm install mongoose
27. Step 1 : Check properly installed or not
Open cmd and type:
•mongod -version
•mongo -version
28. Step 2 : Server on & Client on
Open two separate cmd and type: One for server & another for
client
• mongod
• mongo
29. Within Mongo (Client) window
Shows databases
show dbs
Ans:
admin 0.000GB
config 0.000GB
local 0.000GB
36. MongoDB – sort() Method
• The sort() method specifies the order in which the query returns the
matching documents from the given collection.
db.Collection_Name.sort({filed_name:1 or -1})
db.student.find().sort({age:1})
• Parameter:
The value is 1 or -1 that specifies an ascending or descending
sort respectively. The type of parameter is a document.
37. Connect Node.js with NoSQL MongoDB
Database
Install mongoose:
• Step 1: install the mongoose module. You can install this package by using this
command.
npm install mongoose
• Step 2: Now you can import the mongoose module in your file using:
const mongoose = require('mongoose');
38. Mongoose Module Introduction
•It provides several functions in order to
manipulate the documents of the collection of
the MongoDB database
39. Mongoose
• Mongoose is an Object Data Modeling (ODM) tool designed
to work in an asynchronous environment.
• Mongoose schema as a blueprint for defining the structure
of a Mongoose model that maps directly to a MongoDB
collection.
40. • -->unifiedtopology : DeprecationWarning: current Server Discovery and
Monitoring engine is deprecated, and will be removed in a future version.
• To use the new Server Discover and Monitoring engine, pass option
{ useUnifiedTopology: true } to the MongoClient constructor.
• -->usenewurlparser : DeprecationWarning: current URL string parser is
deprecated, and will be removed in a future version. To use the new parser,
pass option { useNewUrlParser: true } to MongoClient.connect.
41. Step 1 : create schema and set model
const mongoose =require("mongoose")
const url = "mongodb://localhost:27017/project";
const name = new mongoose.Schema({ name: String,
age:Number, rollno:String });
const Name= mongoose.model('Name',name)