MongoDB is a cross-platform document-oriented database that uses JSON-like documents with dynamic schemas. It is classified as a NoSQL database and was developed by MongoDB Inc. in 2007. MongoDB eschews the traditional table-based relational database structure in favor of documents, making integration of certain types of data easier and faster. It provides features like ad-hoc queries, indexing, replication, load balancing and sharding. MongoDB is free and open source and is used by many large companies.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schemaless structures. It is open source and popular, used by many large websites including Craigslist, eBay, Foursquare, and The New York Times. MongoDB eschews the traditional table-based relational database for easier and faster integration of certain application data types.
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 introduction to MongoDB, including:
- MongoDB is a cross-platform document-oriented database that uses documents with a dynamic schema, ad-hoc queries, indexing, replication and sharding.
- Key features include documents, collections, indexes, replication for redundancy and increased availability, and sharding to split data over multiple servers.
- The document discusses setting up a MongoDB instance, replication sets, and sharded clusters.
MongoDB is a document-oriented, schema-free, scalable, high-performance, open-source database that bridges the gap between key-value stores and traditional relational databases. MongoDB uses a document-oriented data model where data is stored in documents that map to programming language data types, which reduces the need for joins. It provides high performance through an absence of joins and support for indexing of embedded documents and arrays.
Open source technologies allow anyone to view, modify, and distribute source code freely. The key characteristics of open source are that it is free to use and modify. Anyone can improve open source code by adding new functionality. As more people contribute code, the potential uses of open source software grow beyond what the original creator intended. To be a web developer requires a passion for learning and skills with technologies like HTML, PHP, Linux, Apache, MySQL, and PHP (LAMP stack). Caching and NoSQL databases like MongoDB can improve performance of dynamic web applications.
The document describes MongoDB, an open-source, high-performance, schema-free, document-oriented database that addresses some shortcomings of relational databases like scalability and flexibility. It discusses some key MongoDB concepts like documents, collections, indexing, embedding data, and querying capabilities. An example blog application is provided to illustrate common operations like creating, retrieving, and counting documents in a MongoDB deployment using PyMongo.
This document provides an overview of MongoDB, including: a brief history of databases from the 1960s to today's NoSQL databases and cloud computing; how MongoDB stores data in databases, collections of documents, and fields; MongoDB's document model for storing data; and basic operations like installation, running the MongoDB shell, saving and retrieving data, replication, and sharding.
This document provides a primer on using MongoDB's find() and aggregate() methods to query data. It explains that find() allows filtering and sorting documents like a SQL SELECT statement, while aggregate() enables more complex queries like joins, aggregations, and outputting results to collections. It details the different stages of aggregation pipelines like match, group, sort, and limit, and provides many examples of using find() and aggregate() to query data in MongoDB.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schemaless structures. It is open source and popular, used by many large websites including Craigslist, eBay, Foursquare, and The New York Times. MongoDB eschews the traditional table-based relational database for easier and faster integration of certain application data types.
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 introduction to MongoDB, including:
- MongoDB is a cross-platform document-oriented database that uses documents with a dynamic schema, ad-hoc queries, indexing, replication and sharding.
- Key features include documents, collections, indexes, replication for redundancy and increased availability, and sharding to split data over multiple servers.
- The document discusses setting up a MongoDB instance, replication sets, and sharded clusters.
MongoDB is a document-oriented, schema-free, scalable, high-performance, open-source database that bridges the gap between key-value stores and traditional relational databases. MongoDB uses a document-oriented data model where data is stored in documents that map to programming language data types, which reduces the need for joins. It provides high performance through an absence of joins and support for indexing of embedded documents and arrays.
Open source technologies allow anyone to view, modify, and distribute source code freely. The key characteristics of open source are that it is free to use and modify. Anyone can improve open source code by adding new functionality. As more people contribute code, the potential uses of open source software grow beyond what the original creator intended. To be a web developer requires a passion for learning and skills with technologies like HTML, PHP, Linux, Apache, MySQL, and PHP (LAMP stack). Caching and NoSQL databases like MongoDB can improve performance of dynamic web applications.
The document describes MongoDB, an open-source, high-performance, schema-free, document-oriented database that addresses some shortcomings of relational databases like scalability and flexibility. It discusses some key MongoDB concepts like documents, collections, indexing, embedding data, and querying capabilities. An example blog application is provided to illustrate common operations like creating, retrieving, and counting documents in a MongoDB deployment using PyMongo.
This document provides an overview of MongoDB, including: a brief history of databases from the 1960s to today's NoSQL databases and cloud computing; how MongoDB stores data in databases, collections of documents, and fields; MongoDB's document model for storing data; and basic operations like installation, running the MongoDB shell, saving and retrieving data, replication, and sharding.
This document provides a primer on using MongoDB's find() and aggregate() methods to query data. It explains that find() allows filtering and sorting documents like a SQL SELECT statement, while aggregate() enables more complex queries like joins, aggregations, and outputting results to collections. It details the different stages of aggregation pipelines like match, group, sort, and limit, and provides many examples of using find() and aggregate() to query data in MongoDB.
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.
Loki is an open source logging aggregation system that indexes the metadata of logs rather than the full contents. It consists of several microservices including the distributor, ingester, query frontend, and querier. The distributor routes logs to the ingesters which store the data in chunks in object storage. The querier handles log queries. Promtail is an agent that can be deployed to scrape logs from files and systemd on servers and ship them to Loki with labels for indexing. Compared to other logging solutions, Loki stores data more cost efficiently and is optimized for scaling.
This document provides an overview of MongoDB including:
- MongoDB is an open-source document database that is schemaless and document-oriented.
- It has advantages like rich querying, horizontal scalability, high availability, and flexibility in schemas.
- The document includes information on MongoDB's data model, querying capabilities, indexing, availability through replication, and scaling through sharding.
- Case studies are presented showing how companies like Mailbox, Visual China, and Youku use MongoDB for applications processing large amounts of data.
Net framework key components - By Senthil Chinnakondatalenttransform
This document provides information on the history and key components of the .NET Framework as well as new features introduced in version 4.5. It began with version 1.0 in 2002 and the latest version is 4.5.2. The .NET Framework includes the Common Language Runtime (CLR) which manages code execution, the Common Type System (CTS) which defines supported data types, and garbage collection for automatic memory management. Version 4.5 introduced improvements such as larger array support, background garbage collection, and regular expression matching timeouts. The document also summarizes WCF concepts like contracts and bindings and describes transport, message, and transport with message credential security options.
Mubashar Iqbal presented on PostgreSQL, an open-source object-relational database system. PostgreSQL prioritizes reliability, security, and standards compliance. It supports Linux, Unix, Windows and is programmed through interfaces like C/C++, Java, .NET, PHP and Python. Common uses include ERP, data warehousing, and network tools. Prominent users include Yahoo, Sony, Reddit, and Skype. Key features include ACID compliance, online backup, point-in-time recovery, and SSL encryption.
Mongo db cluster administration and Shredded DatabasesAbhinav Jha
MongoDB is a non-relations database and well known in the latest trends for storing data in json form.
This slide will help you to understand the advanced concept of MongoDB with the help of sharding.
This slide will cover:
Architecture of sharded cluster.
Query handling in sharded cluster.
Data Distribution Method.
Replica Sets.
This document provides an introduction and overview of the TMS system architecture and MongoDB. It discusses the TMS modules, CDR processing flow, MongoDB features, data model, queries, replica sets, user roles, and monitoring tools. The presentation aims to explain how MongoDB is used in the TMS system and demonstrate common operations.
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
The Digital Enterprise: CIO perspectivesMWD Advisors
This document provides an overview of a survey of CIO perspectives on digital transformation and the key enablers of becoming a digital enterprise. The survey found that CIOs feel they have more work to do in areas like multi-channel customer interactions, the CIO leading digital strategies, real-time analytics, and open data. CIOs saw the top benefits of digital enablers as driving innovation, increasing efficiency and flexibility. The document concludes by advising readers to develop a digital enterprise strategy framework to prioritize digital opportunities and investments.
The document provides an overview of the Word 2013 interface and how to navigate it. Some key points:
- Word 2013 introduces enhancements for collaboration, sharing documents online, and handling PDF content.
- The interface includes elements like the Ribbon, Quick Access Toolbar, document views, and Backstage view for file operations.
- The Ribbon contains tabs and command groups for common tasks. It can be minimized for more screen space.
- Backstage view accessed via the File tab provides options for creating, opening, saving, printing and sharing documents.
- Other areas covered include working with text, formatting, page layout, and printing documents. Concise instructions are provided for common tasks
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
More Than Users workshop for Interaction 17Acuity Design
This document discusses empowering users by connecting them to memories, capacities, and communities through the use of props and objects. It argues that designers should recognize their power and use it to empower users rather than control them. Designers are encouraged to connect users to their memories, capacities, and communities through triggering stories and giving users props to take control of the design process. The goal is to see users as whole people rather than just as individuals by involving their experiences.
This document discusses risk analysis in the food system of Bangladesh. It outlines the national food control structure, which involves 15 ministries and 20 agencies. Risk assessment, management, and communication responsibilities are shared between departments like the Directorate General of Health Services, Department of Livestock Services, and Department of Agriculture Extension. Several foods pose major food safety risks, like fruits/vegetables (pesticides), meat (antibiotics), fish (heavy metals), and milk/eggs (antibiotics). The document reviews laws and standards regarding these foods and monitoring across production and processing stages. It identifies needs like improving baseline data, risk analysis procedures, and regional cooperation on food safety issues.
This report provides a detailed analysis of the global shrimp market and the major requirements for setting up a shrimp processing plant. Analysis covered in this report includes market size, market trends, project cost, machinery, funding, rate of return, profit margins, feedstock requirement, etc. Read full report @ http://www.imarcgroup.com/prefeasibility-report-shrimp-processing-plant
N11 countries or the Next 11 countries refers to a group of eleven countries - specifically Bangladesh, Egypt, Indonesia, Iran, Mexico, Nigeria, Pakistan, the Philippines, Turkey, South Korea, and Vietnam - which have emerging markets that could potentially become some of the world’s largest economies.
The document describes Jan Abernethy's Makers' Club, which was created in 2017. It provides various resources for starting a Makers' Club, including an introduction video, donation suggestions, sample surveys to assess student interests, a promotional video, and links to example club activities and projects. Suggestions are made for obtaining grant funding and additional resources to stock and support the Makerspace. The goal is to provide students with opportunities to collaborate on hands-on projects using materials like Legos, building supplies, and a 3D printer. A special project involved creating a Braille Rubik's Cube for a visually impaired child.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schema flexibility. It is open source and developed by MongoDB Inc., with major websites adopting it as their backend database. MongoDB features include ad-hoc queries, indexing, replication for high availability, load balancing across multiple servers, and support for many programming languages.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schemaless structures. It is open source and popular among major websites for scalability and easy integration of certain application types. MongoDB provides features like replication, sharding, indexing, ad-hoc queries, and scalability across servers.
MongoDB Developer's Notebook, March 2016 -- MongoDB Connector for Business In...Daniel M. Farrell
This document provides instructions for configuring MongoDB, the MongoDB Connector for BI, Eclipse, and Toad to allow running SQL queries against MongoDB from within Eclipse. It describes downloading and installing a Postgres JDBC driver, MongoDB, and the MongoDB Connector for BI. It also covers creating a sample MongoDB database and collection with documents, and configuring Eclipse and Toad to connect to MongoDB via the Connector using the JDBC driver. This will allow running SQL queries from within Eclipse to interact with MongoDB data.
Node Js, AngularJs and Express Js TutorialPHP Support
This document provides an overview of the Node.js, Express.js, AngularJS, and MongoDB technologies and how they can be used together. It discusses what each technology is, its features and uses. Node.js is a JavaScript runtime built on Chrome's V8 engine for building fast network applications. Express.js is a web framework built on Node.js that simplifies building web apps. AngularJS is a JavaScript framework for building dynamic web apps. MongoDB is a popular open-source NoSQL database that stores data in JSON-like documents.
The document discusses setting up fuzzy search capability between MongoDB and Elasticsearch. It describes installing and configuring MongoDB, Elasticsearch, and the Mongo Connector software. The Mongo Connector is used to propagate data changes from MongoDB to Elasticsearch in near real-time so that Elasticsearch can perform searches and queries on the indexed data. Examples are provided for loading test data into MongoDB and verifying the setup.
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.
Loki is an open source logging aggregation system that indexes the metadata of logs rather than the full contents. It consists of several microservices including the distributor, ingester, query frontend, and querier. The distributor routes logs to the ingesters which store the data in chunks in object storage. The querier handles log queries. Promtail is an agent that can be deployed to scrape logs from files and systemd on servers and ship them to Loki with labels for indexing. Compared to other logging solutions, Loki stores data more cost efficiently and is optimized for scaling.
This document provides an overview of MongoDB including:
- MongoDB is an open-source document database that is schemaless and document-oriented.
- It has advantages like rich querying, horizontal scalability, high availability, and flexibility in schemas.
- The document includes information on MongoDB's data model, querying capabilities, indexing, availability through replication, and scaling through sharding.
- Case studies are presented showing how companies like Mailbox, Visual China, and Youku use MongoDB for applications processing large amounts of data.
Net framework key components - By Senthil Chinnakondatalenttransform
This document provides information on the history and key components of the .NET Framework as well as new features introduced in version 4.5. It began with version 1.0 in 2002 and the latest version is 4.5.2. The .NET Framework includes the Common Language Runtime (CLR) which manages code execution, the Common Type System (CTS) which defines supported data types, and garbage collection for automatic memory management. Version 4.5 introduced improvements such as larger array support, background garbage collection, and regular expression matching timeouts. The document also summarizes WCF concepts like contracts and bindings and describes transport, message, and transport with message credential security options.
Mubashar Iqbal presented on PostgreSQL, an open-source object-relational database system. PostgreSQL prioritizes reliability, security, and standards compliance. It supports Linux, Unix, Windows and is programmed through interfaces like C/C++, Java, .NET, PHP and Python. Common uses include ERP, data warehousing, and network tools. Prominent users include Yahoo, Sony, Reddit, and Skype. Key features include ACID compliance, online backup, point-in-time recovery, and SSL encryption.
Mongo db cluster administration and Shredded DatabasesAbhinav Jha
MongoDB is a non-relations database and well known in the latest trends for storing data in json form.
This slide will help you to understand the advanced concept of MongoDB with the help of sharding.
This slide will cover:
Architecture of sharded cluster.
Query handling in sharded cluster.
Data Distribution Method.
Replica Sets.
This document provides an introduction and overview of the TMS system architecture and MongoDB. It discusses the TMS modules, CDR processing flow, MongoDB features, data model, queries, replica sets, user roles, and monitoring tools. The presentation aims to explain how MongoDB is used in the TMS system and demonstrate common operations.
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
The Digital Enterprise: CIO perspectivesMWD Advisors
This document provides an overview of a survey of CIO perspectives on digital transformation and the key enablers of becoming a digital enterprise. The survey found that CIOs feel they have more work to do in areas like multi-channel customer interactions, the CIO leading digital strategies, real-time analytics, and open data. CIOs saw the top benefits of digital enablers as driving innovation, increasing efficiency and flexibility. The document concludes by advising readers to develop a digital enterprise strategy framework to prioritize digital opportunities and investments.
The document provides an overview of the Word 2013 interface and how to navigate it. Some key points:
- Word 2013 introduces enhancements for collaboration, sharing documents online, and handling PDF content.
- The interface includes elements like the Ribbon, Quick Access Toolbar, document views, and Backstage view for file operations.
- The Ribbon contains tabs and command groups for common tasks. It can be minimized for more screen space.
- Backstage view accessed via the File tab provides options for creating, opening, saving, printing and sharing documents.
- Other areas covered include working with text, formatting, page layout, and printing documents. Concise instructions are provided for common tasks
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
More Than Users workshop for Interaction 17Acuity Design
This document discusses empowering users by connecting them to memories, capacities, and communities through the use of props and objects. It argues that designers should recognize their power and use it to empower users rather than control them. Designers are encouraged to connect users to their memories, capacities, and communities through triggering stories and giving users props to take control of the design process. The goal is to see users as whole people rather than just as individuals by involving their experiences.
This document discusses risk analysis in the food system of Bangladesh. It outlines the national food control structure, which involves 15 ministries and 20 agencies. Risk assessment, management, and communication responsibilities are shared between departments like the Directorate General of Health Services, Department of Livestock Services, and Department of Agriculture Extension. Several foods pose major food safety risks, like fruits/vegetables (pesticides), meat (antibiotics), fish (heavy metals), and milk/eggs (antibiotics). The document reviews laws and standards regarding these foods and monitoring across production and processing stages. It identifies needs like improving baseline data, risk analysis procedures, and regional cooperation on food safety issues.
This report provides a detailed analysis of the global shrimp market and the major requirements for setting up a shrimp processing plant. Analysis covered in this report includes market size, market trends, project cost, machinery, funding, rate of return, profit margins, feedstock requirement, etc. Read full report @ http://www.imarcgroup.com/prefeasibility-report-shrimp-processing-plant
N11 countries or the Next 11 countries refers to a group of eleven countries - specifically Bangladesh, Egypt, Indonesia, Iran, Mexico, Nigeria, Pakistan, the Philippines, Turkey, South Korea, and Vietnam - which have emerging markets that could potentially become some of the world’s largest economies.
The document describes Jan Abernethy's Makers' Club, which was created in 2017. It provides various resources for starting a Makers' Club, including an introduction video, donation suggestions, sample surveys to assess student interests, a promotional video, and links to example club activities and projects. Suggestions are made for obtaining grant funding and additional resources to stock and support the Makerspace. The goal is to provide students with opportunities to collaborate on hands-on projects using materials like Legos, building supplies, and a 3D printer. A special project involved creating a Braille Rubik's Cube for a visually impaired child.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schema flexibility. It is open source and developed by MongoDB Inc., with major websites adopting it as their backend database. MongoDB features include ad-hoc queries, indexing, replication for high availability, load balancing across multiple servers, and support for many programming languages.
MongoDB is a cross-platform document-oriented database that uses dynamic schemas and stores data in JSON-like documents with schemaless structures. It is open source and popular among major websites for scalability and easy integration of certain application types. MongoDB provides features like replication, sharding, indexing, ad-hoc queries, and scalability across servers.
MongoDB Developer's Notebook, March 2016 -- MongoDB Connector for Business In...Daniel M. Farrell
This document provides instructions for configuring MongoDB, the MongoDB Connector for BI, Eclipse, and Toad to allow running SQL queries against MongoDB from within Eclipse. It describes downloading and installing a Postgres JDBC driver, MongoDB, and the MongoDB Connector for BI. It also covers creating a sample MongoDB database and collection with documents, and configuring Eclipse and Toad to connect to MongoDB via the Connector using the JDBC driver. This will allow running SQL queries from within Eclipse to interact with MongoDB data.
Node Js, AngularJs and Express Js TutorialPHP Support
This document provides an overview of the Node.js, Express.js, AngularJS, and MongoDB technologies and how they can be used together. It discusses what each technology is, its features and uses. Node.js is a JavaScript runtime built on Chrome's V8 engine for building fast network applications. Express.js is a web framework built on Node.js that simplifies building web apps. AngularJS is a JavaScript framework for building dynamic web apps. MongoDB is a popular open-source NoSQL database that stores data in JSON-like documents.
The document discusses setting up fuzzy search capability between MongoDB and Elasticsearch. It describes installing and configuring MongoDB, Elasticsearch, and the Mongo Connector software. The Mongo Connector is used to propagate data changes from MongoDB to Elasticsearch in near real-time so that Elasticsearch can perform searches and queries on the indexed data. Examples are provided for loading test data into MongoDB and verifying the setup.
MongoDB is a high-performance, open-source document database that provides high availability, easy scalability, and uses dynamic schemas. It stores data in flexible, JSON-like documents, meaning fields can vary from document to document and data structure can change over time. MongoDB is commonly used for big data and real-time applications.
I recently took the MongoDB DBA certification exam, and was caught unprepared by questions related to mongofiles, mongoperf, and more. What have I been missing by not using these utilities ?
What is the significance of MongoDB and what are its usages.docxkzayra69
MongoDB's significance lies in its ability to handle diverse data types, scale easily, and support agile development practices, making it a valuable asset for organizations looking to manage and analyze large volumes of data efficiently. Its dynamic schema and querying capabilities make it suitable for various use cases such as content management systems, social networking applications, IoT data storage, and mobile app backends. To fully leverage MongoDB's capabilities, it's essential to understand how to configure resource utilization effectively. By following best practices for hardware sizing, storage engine configuration, index optimization, and replica sets/sharding, you can ensure optimal performance and scalability for your MongoDB deployment. MongoDB provides built-in tools such as mongoimport and mongoexport for importing and exporting data, as well as monitoring tools like mongostat and mongotop for monitoring server statistics and database operations. By monitoring disk usage using MongoDB's built-in tools, database profiling, operating system tools, and third-party monitoring solutions, you can proactively identify and address issues affecting disk performance and ensure the smooth operation of your MongoDB deployment.
MongoDB is an open-source, cross-platform document-oriented database written in C++. It provides high performance, high availability, and automatic scaling. MongoDB stores data as documents with dynamic schemas, making it flexible and suitable for big data and real-time applications. It supports features like ad-hoc queries, indexing, replication, sharding, and map-reduce for aggregation.
how_can_businesses_address_storage_issues_using_mongodb.pdfsarah david
MongoDB is an open-source database that can help businesses address storage issues. It provides scalability, availability, and handles large amounts of data well. MongoDB uses a flexible document data model and has features like replication, sharding, and indexing that improve performance. While it has advantages like flexibility, simplicity, and speed, it also has drawbacks like limited transactions and joins compared to relational databases. Understanding both the benefits and limitations of MongoDB is important for businesses evaluating it for their data storage needs.
how_can_businesses_address_storage_issues_using_mongodb.pptxsarah david
MongoDB enables seamless data storage and performance. Explore our blog to learn how MongoDB handles storage issues for startups and large-scale enterprises. Discover how to optimize MongoDB performance using open-source database storage.
Introduction to MongoDB and its best practicesAshishRathore72
This document provides a summary of a presentation on MongoDB best practices. It discusses MongoDB concepts like data modeling, CRUD operations, querying, and aggregation. It also covers topics like MongoDB security, scaling options, real-world use cases, and best practices for hardware, schema design, indexing, and scalability. The presentation provides an overview of using MongoDB effectively.
- The document discusses the differences between MongoDB Operations Manager, MongoDB Cloud Manager, and MongoDB Atlas for managing a MongoDB database server on a private multi-national cloud.
- It recommends using a sharded MongoDB topology to store each country's data locally due to data locality laws while allowing a single view of data across countries.
- It provides an overview of cloud computing, Platform as a Service (PaaS), and suggests using Cloud Foundry as a PaaS for automatically deploying, configuring, scaling, and managing applications on the cloud.
MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. It stores data in flexible, JSON-like documents, enabling storage of data with complex relationships easily and supporting polyglot persistence. MongoDB can be used for applications such as content management systems, user profiles, logs, and more. It provides indexing, replication, load balancing and aggregation capabilities.
Mongo db pefrormance optimization strategiesronwarshawsky
The document discusses MongoDB performance optimization strategies. It outlines various techniques such as using map-reduce operations, updating to the latest MongoDB version, implementing sharding, balancing shards, optimizing disk input/output, managing locks, using capped collections for fast writes, leveraging natural ordering for fast reads, considering query performance including indexes, minimizing document size through field name shortening, and keeping MongoDB updates. It also briefly describes Enteros' software for database problem root cause analysis across infrastructure tiers.
This document provides an overview of MongoDB and discusses its installation and configuration on Windows systems. It covers downloading the appropriate MongoDB version, installing the downloaded file, setting up the MongoDB environment by creating a data directory and log files, and connecting to MongoDB using the mongo shell. The document is divided into multiple sections covering MongoDB's features, data modeling using documents, database and collection management operations, and connecting to MongoDB from Java applications.
MongoDB is a document database that provides high performance, high availability, and easy scalability through embedding, indexing, replication, and sharding. It uses a dynamic schema which allows polymorphism and flexible data structures. MongoDB stores data as documents with dynamic schema in BSON format and provides CRUD operations through methods like insert(), find(), update(), and remove(). It can be deployed in standalone, replica set, or sharded cluster configurations for scaling.
MongoDB is a cross-platform document-oriented database program that uses JSON-like documents with dynamic schemas, commonly referred to as a NoSQL database. It allows for embedding of documents and arrays within documents, hierarchical relationships between data, and indexing of data for efficient queries. MongoDB is developed by MongoDB Inc. and commonly used for big data and content management applications due to its scalability and ease of horizontal scaling.
This is an introduction about the MongoDB. It includes basic MongoQueries. Not a advance level of presentation but provide nice information for the starters
The document provides tips and suggestions for creating effective presentation slides, including:
- Using few words on each slide and letting pictures convey information
- Avoiding distracting backgrounds and fonts that are hard to read
- Explaining any graphics or animations used
- Practicing the presentation to avoid filler words and ensure proper timing
It also warns against common pitfalls like reading the slides verbatim, having too much text on slides, or flipping between slides without explanation.
The document provides an overview of the Document Object Model (DOM) and how JavaScript can be used to manipulate the DOM. It discusses how the DOM used to be browser-specific but is now a standard that can be manipulated by various languages. It provides examples of DOM tree structure, referencing DOM objects by ID, and manipulating DOM properties like innerHTML and visibility. The document is intended as a tutorial for learning the DOM and JavaScript DOM manipulation.
This document is the preface to a mathematics textbook for 10th standard students in Tamil Nadu, India. It outlines the goals of revising the textbook to implement a uniform curriculum across all school streams and improve mathematics education. It emphasizes that mathematics is essential for science, technology, and individual growth. The preface notes that the textbook aims to help students grasp fundamentals and apply them to problem solving. It also stresses the importance of the teacher's role in guiding students and making learning learner-centered. The textbook contents are arranged logically with examples to provide practice for thorough understanding.
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
This collection of fairy tales promises to transport readers to fantastical worlds full of old-world charm and mysticism. It includes many free tales for kids, with pictures, from KidsGen which aims to be a top site for new age children. The stories are meant to allow readers to lose themselves in far away fantasies and feel nostalgia.
A queen was told by a fairy that her daughter would bring her woe, so she attached a hawthorn branch to the newborn princess's head, turning her into a monkey. The monkey was raised by the queen's nephew but later captured by monkey king Magot who wanted to marry her. She refused and fled, transforming back into a princess after opening a magic chest. She fell in love with her cousin, but was imprisoned by the fairy. He rescued her and they married, reconciling their kingdoms.
This document provides an overview of commonly used features in PowerPoint. It demonstrates how to add and format slides, apply themes, vary text formatting, insert images from clipart or files, add animated and timed text, apply slide transitions and sounds, use shapes and diagrams, embed videos, add action buttons for navigation, and link to web content and email addresses. The goal is to serve as both a user guide and example presentation to learn PowerPoint features.
The document provides an overview of reporting and analytics capabilities in Sprinklr. It describes navigating between standard dashboards, setting filters and date ranges, and customizing dashboards. Standard dashboards track metrics like campaigns, social engagement, inbound/outbound tags, and service level agreements. Custom dashboards can be created and shared with other users. The document contains step-by-step instructions for using various reporting features in Sprinklr.
This collection of fairy tales promises to transport readers to fantastical worlds with old-world charm and mysticism. It includes many free tales for kids, with pictures, from KidsGen which aims to be a top site for new age kids to enjoy stories and lose themselves in far away fantasies or feel nostalgia.
This document contains a collection of mathematical puzzles posed by the famous Indian mathematician Shakuntala Devi. It includes 26 puzzles of varying difficulty levels that involve topics like ratios, proportions, averages, time calculations, and logical reasoning. The goal is to sharpen readers' intellectual faculties by challenging them to work through the puzzles to find the solutions. Shakuntala Devi was known as a "human computer" for her incredible calculating abilities and authored several books on mathematics.
A queen was told by a fairy that her daughter would bring her woe, so she attached a hawthorn branch to the newborn princess's head, turning her into a monkey. The monkey was raised by the queen's nephew but later captured by monkey king Magot who wanted to marry her. She refused and fled, transforming back into a princess after opening a magic chest. She fell in love with her cousin, but was imprisoned by the fairy. He rescued her and they married, reconciling their kingdoms.
Graffiti refers to writings or drawings created illicitly on walls or other surfaces in public places. Graffiti has existed since ancient times but modern graffiti most commonly uses spray paint and markers. While graffiti was historically found in ancient Egypt, Greece, and Rome, today creating graffiti without property owner consent is generally considered defacement or vandalism, punishable by law.
Graffiti refers to writings or drawings created illicitly on walls or other surfaces. Graffiti has existed since ancient times but modern graffiti most commonly uses spray paint or markers. While graffiti was a common form of expression historically, today most countries consider unauthorized graffiti on private property to be vandalism and defacement, which is punishable by law.
This one sentence document does not provide enough context or information to create an accurate 3 sentence summary. The document contains only one word - "Lorem" - which is not meaningful on its own.
This document provides an introduction to HTML basics. It covers using HTML tags to structure a web page with headings, paragraphs, and other text elements. It explains how to add images, tables, colors and hyperlinks to an HTML page. The document also discusses HTML tags, elements, attributes and entities. It encourages using logical tags over physical tags and style sheets for formatting. It includes examples and instructions for creating a basic HTML page using a text editor and viewing it in a browser.
This one sentence document does not provide enough context or information to create an accurate 3 sentence summary. The document contains only one word - "Lorem" - which is not meaningful on its own.
BLAST is a novel presentation format that encourages rapid knowledge transfer through short slides of 8 words or less to avoid "death by powerpoint". It aims to efficiently convey key information in a brief format. The presentation and additional references on the BLAST format can be found at blast.emcrit.org.
1. MongoDB
From Wikipedia, the free encyclopedia
MongoDB
MongoDB Logo.png
Developer(s) MongoDB Inc.
Initial release 2009
Stable release 2.4.8 / 1 November 2013
Preview release 2.5.2 / 26 August 2013
Development status Active
Written in C++
Operating system Cross-platform
Available in English
Type Document-oriented database
License GNU AGPL v3.0 (drivers: Apache license)
Website www.mongodb.org
MongoDB (from "humongous") is a cross-platform document-oriented database
system. Classified as a NoSQL database, MongoDB eschews the traditional table-
based relational database structure in favor of JSON-like documents with dynamic
schemas (MongoDB calls the format BSON), making the integration of data in
certain types of applications easier and faster. Released under a combination of
the GNU Affero General Public License and the Apache License, MongoDB is free
and open source software.
First developed by 10gen (now MongoDB Inc.) in October 2007 as a component of a
planned platform as a service product, the company shifted to an open source
development model in 2009, with 10gen offering commercial support and other
services.[1] Since then, MongoDB has been adopted as backend software by a
number of major websites and services, including Craigslist, eBay, Foursquare,
SourceForge, and The New York Times, among others. MongoDB is the most popular
NoSQL database system.[2]
Contents [hide]
1 History
2 Licensing and support
3 Main features
4 Criticisms
5 Language support
6 Management and graphical front-ends
6.1 MongoDB tools
7 Production Deployments
8 See also
9 References
10 Bibliography
11 External links
History[edit]
Development of MongoDB began in 2007, when the company (then named 10gen) was
building a platform as a service similar to Windows Azure or Google App Engine.
[3] In 2009, MongoDB was open sourced as a stand-alone product[4] with an AGPL
license.
From version 1.4 (March 2010), MongoDB has been considered production ready.[5]
The latest stable version, 2.4.8, was released on November 1, 2013.
Licensing and support[edit]
MongoDB is available for free under the GNU Affero General Public License.[4]
The language drivers are available under an Apache License. In addition, MongoDB
Inc. offers commercial licenses for MongoDB.gh[6]
Main features[edit]
The following is a brief summary of some of the main features:[7]
Ad hoc queries
MongoDB supports search by field, range queries, regular expression searches.
Queries can return specific fields of documents and also include user-defined
JavaScript functions.
Indexing
2. Any field in a MongoDB document can be indexed (indices in MongoDB are
conceptually similar to those in RDBMSes). Secondary indices are also available.
Replication
MongoDB provides high availability and increased throughput with replica sets.
[8] A replica set consists of two or more copies of the data. Each replica may
act in the role of primary or secondary replica at any time. The primary replica
performs all writes and reads by default. Secondary replicas maintain a copy of
the data on the primary using built-in replication. When a primary replica
fails, the replica set automatically conducts an election process to determine
which secondary should become the primary. Secondaries can also perform read
operations, but the data is eventually consistent by default.
Load balancing
MongoDB scales horizontally using sharding.[9] The user chooses a shard key,
which determines how the data in a collection will be distributed. The data is
split into ranges (based on the shard key) and distributed across multiple
shards. (A shard is a master with one or more slaves.)
MongoDB can run over multiple servers, balancing the load and/or duplicating
data to keep the system up and running in case of hardware failure. Automatic
configuration is easy to deploy, and new machines can be added to a running
database.
File storage
MongoDB can be used as a file system, taking advantage of load balancing and
data replication features over multiple machines for storing files.
This function, called GridFS,[10] is included with MongoDB drivers and available
with no difficulty for development languages (see "Language Support" for a list
of supported languages). MongoDB exposes functions for file manipulation and
content to developers. GridFS is used, for example, in plugins for NGINX[11] and
lighttpd.[12]
In a multi-machine MongoDB system, files can be distributed and copied multiple
times between machines transparently, thus effectively creating a load balanced
and fault tolerant system.
Aggregation
MapReduce can be used for batch processing of data and aggregation operations.
The aggregation framework enables users to obtain the kind of results for which
the SQL GROUP BY clause is used.
Server-side JavaScript execution
JavaScript can be used in queries, aggregation functions (such as MapReduce),
and sent directly to the database to be executed.
Capped collections
MongoDB supports fixed-size collections called capped collections. This type of
collection maintains insertion order and, once the specified size has been
reached, behaves like a circular queue.
Criticisms[edit]
MongoDB uses a readers-writer lock that allows concurrent read access to a
database but exclusive write access to a single write operation.[13] Before
version 2.2, this lock was implemented on a per-mongod basis. Since version 2.2,
the lock is implemented at the database level.[14] One approach to increase
concurrency is to use sharding.[15] In some situations, reads and writes will
yield their locks. If MongoDB predicts a page is unlikely to be in memory,
operations will yield their lock while the pages load. The use of lock yielding
expanded greatly in 2.2.[16]
Another criticism related to scalability is that only 2GB of memory may be used
on 32-bit systems, rather than the 4GB theoretically available; more memory is
available on 64-bit systems.[17] In some cases, this was due to the use of
MongoDB on 32-bit systems and their inherent memory limitations.[18] MongoDB
recommends users provide sufficient RAM for their working set.[19] Some users
encounter issues when their working set exceeds available RAM and the system
encounters page faults. MongoHQ, a provider of managed MongoDB infrastructure,
recommends a scaling checklist for large systems.[20]
Language support[edit]
MongoDB has official drivers for a variety of popular programming languages and
development environments.[21] Web programming language Opa also has built-in
3. support for MongoDB, which is tightly integrated in the language and offers a
type-safety layer on top of MongoDB.[22] There are also a large number of
unofficial or community-supported drivers for other programming languages and
frameworks.[21]
Management and graphical front-ends[edit]
MongoDB tools[edit]
In a MongoDB installation the following commands are available:
mongo
MongoDB offers an interactive shell called mongo,[23] which lets developers
view, insert, remove, and update data in their databases, as well as get
replication information, set up sharding, shut down servers, execute JavaScript,
and more.
Administrative information can also be accessed through a web interface,[24] a
simple webpage that serves information about the current server status. By
default, this interface is 1000 ports above the database port (28017).
mongostat
mongostat[25] is a command-line tool that displays a summary list of status
statistics for a currently running MongoDB instance: how many inserts, updates,
removes, queries, and commands were performed, as well as what percentage of the
time the database was locked and how much memory it is using. This tool is
similar to the UNIX/Linux vmstat utility.
mongotop
mongotop[26] is a command-line tool providing a method to track the amount of
time a MongoDB instance spends reading and writing data. mongotop provides
statistics on the per-collection level. By default, mongotop returns values
every second. This tool is similar to the UNIX/Linux top utility.
mongosniff
mongosniff[27] is a command-line tool providing a low-level tracing/sniffing
view into database activity by monitoring (or "sniffing") network traffic going
to and from MongoDB. mongosniff requires the Libpcap network library and is only
available for Unix-like systems. A cross-platform alternative is the open source
Wireshark packet analyzer which has full support for the MongoDB wire protocol.
mongoimport, mongoexport
mongoimport[28] is a command-line utility to import content from a JSON, CSV, or
TSV export created by mongoexport[29] or potentially other third-party data
exports.
mongodump, mongorestore
mongodump[30] is a command-line utility for creating a binary export of the
contents of a Mongo database; mongorestore[31] can be used to reload a database
dump.
Production Deployments[edit]
Some of the prominent users of MongoDB include:[32]
MetLife uses MongoDB for “The Wall," a customer service application providing a
"360-degree view" of MetLife customers.[33]
Craigslist stores over 2 billion records in MongoDB.[34]
SAP uses MongoDB in the SAP PaaS.[35]
Forbes stores articles and companies data in MongoDB.[36]
The New York Times uses MongoDB in its form-building application for photo
submissions.[37]
Sourceforge uses MongoDB for its back-end storage pages.[38]
Codecademy[39]
Shutterfly uses MongoDB for its photo platform. As of 2013, the photo platform
stores 18 billion photos uploaded by Shutterfly's 7 million users.[40][41]
The Guardian uses MongoDB for its identity system.[42]
CERN uses MongoDB as the primary back-end for the Data Aggregation System for
the Large Hadron Collider.[43]
Foursquare deploys MongoDB on Amazon AWS to store venues and user check-ins into
venues.[44]
eBay uses MongoDB in the search suggestion and the internal Cloud Manager State
Hub.[45]
See also[edit]
4. Portal icon Free software portal
Apache's Erlang-based CouchDB (open source)
Apache's Cassandra (open source)
Apache's Java-based HBase and Accumulo (open source)
Basho Riak (open source, Apache License 2.0)
TokuMX performance engine for MongoDB (open source)
Apache's Java-based ElasticSearch (open source)
References[edit]
Jump up ^ "10gen embraces what it created, becomes MongoDB Inc.". Gigaom.
Retrieved 27 August 2013.
Jump up ^ "DB-Engines Ranking". Retrieved 8 September 2013.
Jump up ^ MongoDB daddy: My baby beats Google BigTable
^ Jump up to: a b The MongoDB NoSQL Database Blog, The AGPL
Jump up ^ The MongoDB NoSQL Database Blog, MongoDB 1.4 Ready for Production
Jump up ^ MongoDB Support by 10gen
Jump up ^ MongoDB Developer Manual
Jump up ^ [1]
Jump up ^ [2]
Jump up ^ GridFS article on MongoDB Developer's Manual
Jump up ^ NGINX plugin for MongoDB source code
Jump up ^ lighttpd plugin for MongoDB source code
Jump up ^ FAQ: Concurrency
Jump up ^ FAQ Concurrency - How Granular Are Locks
Jump up ^ FAQ Concurrency - How Does Sharding Affect Concurrency
Jump up ^ FAQ Concurrency - Do Operations Ever Yield the Lock
Jump up ^ 32-bit Limitations
Jump up ^ Does Everybody Hate MongoDB
Jump up ^ What is the Working Set
Jump up ^ Optimizing Your MongoDB Dataset
^ Jump up to: a b "MongoDB Drivers and Client Libraries “ MongoDB Ecosystem
2.2.2". Mongodb.org. Retrieved 2013-07-08.
Jump up ^ / (2012-11-27). "The database · MLstate/opalang Wiki · GitHub".
Github.com. Retrieved 2013-07-08.
Jump up ^ mongo - The Interactive Shell
Jump up ^ HTTP Console
Jump up ^ mongostat Manual
Jump up ^ mongotop Manual
Jump up ^ mongosniff Manual
Jump up ^ mongoimport Manual
Jump up ^ mongoexport Manual
Jump up ^ mongodump Manual
Jump up ^ mongorestore Manual
Jump up ^ Production Deployments
Jump up ^ MetLife Uses NoSQL For Customer Service Breakthrough
Jump up ^ Lessons Learned from Migrating 2+ Billion Documents at Craigslist
Jump up ^ The Quest to Understand the Use of MongoDB in the SAP PaaS
Jump up ^ Supporting Distributed Global Workforce of Contributors with MongoDB
Jump up ^ NYT + MongoDB in Production
Jump up ^ Scaling SourceForge with MongoDB
Jump up ^ How Codeacademy is Using MongoDB
Jump up ^ Real World NoSQL: MongoDB at Shutterfly
Jump up ^ Here's How We Think Of Shutterfly's Stock Value
Jump up ^ MongoDB at The Guardian
Jump up ^ Holy Large Hadron Collider, Batman!
Jump up ^ Experiences Deploying MongoDB on AWS
Jump up ^ MongoDB at eBay
Bibliography[edit]
Banker, Kyle (March 28, 2011), MongoDB in Action (1st ed.), Manning, p. 375,
ISBN 978-1-935182-87-0
Chodorow, Kristina; Dirolf, Michael (September 23, 2010), MongoDB: The
Definitive Guide (1st ed.), O'Reilly Media, p. 216, ISBN 978-1-4493-8156-1
Pirtle, Mitch (March 3, 2011), MongoDB for Web Development (1st ed.), Addison-
5. Wesley Professional, p. 360, ISBN 978-0-321-70533-4
Hawkins, Tim; Plugge, Eelco; Membrey, Peter (September 26, 2010), The Definitive
Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing (1st ed.),
Apress, p. 350, ISBN 978-1-4302-3051-9
External links[edit]
Official website
MongoDB Manual
Designing for the Cloud at MIT Technology Review
A vendor-independent comparison of NoSQL databases: Cassandra, HBase, MongoDB,
Riak (NetworkWorld)
Categories: Free database management systemsDocument-oriented
databasesDistributed computing architectureStructured storageNoSQL
Navigation menu
Create accountLog inArticleTalkReadEditView history
Search
Main page
Contents
Featured content
Current events
Random article
Donate to Wikipedia
Interaction
Help
About Wikipedia
Community portal
Recent changes
Contact page
Tools
Print/export
Languages
???????
?????????
Català
Deutsch
Español
?????
Français
???
???????
Bahasa Indonesia
Italiano
Magyar
Nederlands
???
Polski
Português
???????
?????
Türkçe
??????????
??
Edit links
This page was last modified on 12 December 2013 at 18:05.
Text is available under the Creative Commons Attribution-ShareAlike License;
additional terms may apply. By using this site, you agree to the Terms of Use
and Privacy Policy.
Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-
profit organization.
Privacy policyAbout WikipediaDisclaimersContact WikipediaDevelopersMobile
viewWikimedia Foundation Powered by MediaWiki
6. Wesley Professional, p. 360, ISBN 978-0-321-70533-4
Hawkins, Tim; Plugge, Eelco; Membrey, Peter (September 26, 2010), The Definitive
Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing (1st ed.),
Apress, p. 350, ISBN 978-1-4302-3051-9
External links[edit]
Official website
MongoDB Manual
Designing for the Cloud at MIT Technology Review
A vendor-independent comparison of NoSQL databases: Cassandra, HBase, MongoDB,
Riak (NetworkWorld)
Categories: Free database management systemsDocument-oriented
databasesDistributed computing architectureStructured storageNoSQL
Navigation menu
Create accountLog inArticleTalkReadEditView history
Search
Main page
Contents
Featured content
Current events
Random article
Donate to Wikipedia
Interaction
Help
About Wikipedia
Community portal
Recent changes
Contact page
Tools
Print/export
Languages
???????
?????????
Català
Deutsch
Español
?????
Français
???
???????
Bahasa Indonesia
Italiano
Magyar
Nederlands
???
Polski
Português
???????
?????
Türkçe
??????????
??
Edit links
This page was last modified on 12 December 2013 at 18:05.
Text is available under the Creative Commons Attribution-ShareAlike License;
additional terms may apply. By using this site, you agree to the Terms of Use
and Privacy Policy.
Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-
profit organization.
Privacy policyAbout WikipediaDisclaimersContact WikipediaDevelopersMobile
viewWikimedia Foundation Powered by MediaWiki