Introduction to Nodejs and Isomorphic javascriptChenKuo Chen
ย
This document discusses asynchronous programming, Node.js, and isomorphic JavaScript web frameworks. It describes how Node.js uses asynchronous and event-driven programming to handle requests without blocking. It also explains how isomorphic frameworks allow JavaScript code to run on both the client-side and server-side, allowing code reuse and initial page rendering from the server. Traditional frameworks are compared to single page applications and how isomorphic frameworks address some of the challenges with SEO and duplicate code.
Brief overview of TypeScript - Ljubljana JavaScript Users GroupPeter A. Pirc
ย
A very short overview of TypeScript language, presented on first Ljubljana JavaScript Users Group meetup on 30th April 2013.
Video can be found at http://bit.ly/papslts
This document discusses strategies for promoting MongoDB adoption. It recommends understanding MongoDB's features, costs, and use cases before promoting it to potential users. It suggests identifying pain points like complex joins that MongoDB could alleviate for "developers" and performance needs that its MapReduce could address for "managers." Examples of successful MongoDB migrations are presented to convince "skeptics." The goal is to alter perceptions and infect target organizations with MongoDB by solving real problems rather than just touting its features.
MongoDB is an open-source, schema-free, document-oriented database that provides high performance, flexibility and scalability. It uses JSON-like documents with dynamic schemas, instead of the traditional table-based relational database structure. MongoDB is especially useful for web applications, caching, and scaling to handle large volumes of data. While it is less suited to highly transactional workloads or problems requiring SQL, MongoDB provides a simple interface and scales horizontally across commodity servers.
The document discusses NoSQL databases and describes MongoDB as an open-source, high-performance, schema-free, document-oriented database. It provides an overview of MongoDB's data model using documents and collections, and examples of common operations like creating, querying, and indexing documents.
Node.js is a JavaScript runtime environment that uses Google Chrome's V8 engine. It allows for high concurrency without threads or processes by using an event loop and callbacks for non-blocking I/O. While it can be used for server-side JavaScript applications, its lack of access to the DOM from the server-side presents some drawbacks compared to traditional client-side JavaScript. Overall, Node.js enables highly scalable applications but its non-blocking nature requires some adjustment for developers accustomed to blocking I/O models.
The Stack Exchange infrastructure supports 560 million page views and 34TB of data transferred per month across 1665 requests per second on average. To ensure high performance, Stack Exchange uses load balancers, web servers, caching, and databases in a redundant configuration. Careful performance monitoring and optimization has resulted in homepage and question page render times of 52ms and 33ms respectively.
Ryuji Tamagawa gave a presentation on using MongoDB. He introduced MongoDB as a hybrid of NoSQL and SQL that scales easily. To improve performance on AWS, one must understand MongoDB's memory management, the application's workload pattern, and the size of "hot" data that is frequently accessed. MongoDB does not manage memory itself, instead using memory mapping to leverage the OS buffer. It is important to give the OS enough memory to store hot data and account for indexes. Replication can be used to distribute data across multiple instances for high availability. Performance tests showed SSD-backed instance types had faster write times than non-SSD types for storing Wikipedia data in MongoDB.
This talk will cover lessons learned at Community Engine regarding MongoDB, including: why we moved away from an Hybrid solution using SQL and MongoDB; an outline of the technologies and what we learned using MongoDB on Amazon Web Services; the MongoDB C# driver; MongoDB with SOLR for Full Text Search; how we do migration, deployment and more.
This document discusses MongoDB replication, sharding, and aggregation. It explains that replica sets allow for high availability and redundancy through primary-secondary replication across multiple servers. Sharding partitions data by shard key across multiple replica sets to scale databases horizontally. The aggregation framework provides data aggregation capabilities through pipelines of operations like match, project, group, and sort.
Presentation on MongoDB given at the Hadoop DC meetup in October 2009. Some of the slides at the end are extra examples that didn't appear in the talk, but might be of interest.
Vlad zelinschi optimizing the critical rendering pathCodecamp Romania
ย
The document discusses optimizing the critical rendering path (CRP) of a web page. The CRP refers to the steps between receiving HTML, CSS, and JavaScript and rendering pixels on the screen. These steps include parsing HTML to build the DOM tree, parsing CSS to build the CSSOM tree, combining them into a render tree, running layout to compute geometry, and painting to the screen. Optimizing the CRP means minimizing the time spent in these steps. Some tips include getting CSS to the client fast, eliminating blocking JavaScript from the CRP, and focusing on above-the-fold content. Tools like critical CSS extraction can help optimize the CRP.
Porting ASP.NET applications to Windows AzureGunnar Peipman
ย
Hosting applications on Windows Azure is simple but there are things to change when cloud-enabling existing web applications because cloud is conceptually different than on-premises or shared hosting environment. This sessions goes through main issues one will face when moving applications to cloud. Real-life examples provide elegant solutions to problems and through demos the audience will see how to deploy applications to cloud and how to test and run cloud and hybrid applications on your development machine.
This document discusses remodel, an ORM that maps Ruby objects to Redis to provide fast and scalable data storage. It highlights that remodel is faster than MySQL for read and write operations since it stores data in memory instead of disk. The document demonstrates remodel's features like associations and basic validations and notes its current alpha status and roadmap for improvements.
AJAX allows for asynchronous data retrieval and dynamic display. It uses technologies like XML, XSLT, DOM, and JavaScript. Servlet 3.0 includes annotations and methods to support asynchronous processing, allowing requests to be processed asynchronously without blocking the original thread. The AsyncContext class provides an execution context for asynchronous operations and wraps the request and response.
The document discusses factors that affect website performance, including front-end elements like CSS, JavaScript, images, and back-end elements like caching, threading, and database queries. It notes that only 10-20% of response time is spent on downloading HTML, so focus should be on optimizing other parts of the page load. It also outlines the anatomy of an HTTP request and lists 14 rules for improving performance, such as reducing HTTP requests, using content delivery networks, gzipping components, and making AJAX cacheable. It emphasizes that teams should regularly audit performance and prioritize optimizations.
This document provides an agenda for a presentation on MongoDB. It introduces MongoDB as a popular open-source NoSQL database that uses a document-oriented data model with dynamic schemas like JSON. The presentation will cover NoSQL concepts, MongoDB fundamentals including BSON and examples, and include a hands-on section working with MongoDB. It is aimed at developers interested in learning about using MongoDB for data storage.
This document provides an overview of Bower, a package manager for the web. It discusses the requirements to use Bower, how to install and configure it, and how to run Bower to install dependencies. Bower is used to manage front-end components and their dependencies. It requires Node.js and NPM to be installed first. Then Bower can be installed globally and configured via a bower.json file to specify packages and dependencies. Running Bower will install all dependencies to the default or specified directory. The document also briefly explains how Bower can be used with XPages projects to manage front-end libraries.
When someone wants to learn about Microservice, s/he can easily get lost in the jungle of buzzwords. Specially the relationship between Domain Design, Service to Service communication and Devops are used very frequently in Microservice. But which is what and how are they fit together?
I tried to discuss them in my presentation.
Video can be found here: https://www.youtube.com/playlist?list=PLEYpvDF6qy8YyX2dQX93C88mQ5alaWFXJ
This document provides an introduction to the MEAN stack for beginners. It discusses JavaScript standards and Node.js for the backend using Express.js. It also covers MongoDB as a NoSQL database and its advantages over relational databases. Finally, it discusses Angular as a frontend framework for building single page applications, its core concepts and advantages over other frameworks. The document aims to give beginners an overview of each technology that makes up the MEAN stack.
A talk given at the Infrastructure Coders Meetup in Canberra May 2018.
This presentation gives an overview of the Hyperledger projects in general and some closer look at Hyperledger Fabric and how to deploy it to AWS.
Two deployment options are explored: AWS Blockchain Template and Hyperledger Cello Ansible Agent.
Progressive Web Apps Nedir? JavaScript Service Workers Nedir?Mehmet Seven
ย
Service workers allow web applications to work offline by intercepting network requests and serving cached responses. They load in the background and can handle fetch events even when the web page or browser tab is closed. Service workers enable features like push notifications, background syncing, and caching of pages and files to improve performance and user experience for progressive web apps.
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage EngineMongoDB
ย
An Update on MongoDB's WiredTiger Storage Engine
Keith Bostic, Senior Staff Engineer, MongoDB
MongoDB Evenings Boston
Brightcove Offices
September 29, 2016
This document summarizes a presentation about MongoDB given by Sean Laurent of StudyBlue, Inc. It introduces MongoDB and its features, including its document-oriented data model, flexible schemas, querying and updating capabilities, indexing, drivers, replication and sharding for scalability. Useful MongoDB tools are also discussed like the mongo shell, mongostat, mongotop and MMS monitoring. The document concludes with MongoDB's strengths like horizontal scaling and rapidly evolving schemas, and weaknesses like not being a drop-in replacement for SQL and limitations around transactions.
This document provides an overview and introduction to MongoDB. It discusses what MongoDB is, its features such as being schemaless and document-oriented, and how to install MongoDB. It also covers JSON and BSON formats and compares MongoDB to traditional RDBMS systems. The document recommends MongoDB for non-transactional applications and warns against using it for highly transactional or SQL-required problems.
The document discusses using the MongoDB shell for debugging, testing, and administration tasks. It notes some limitations of using JavaScript in the shell, such as number and date handling. It provides examples of common shell commands like insert, update, remove, loading scripts, running commands, and profiling. Useful shell functions are also demonstrated like printjson and forEach. The document concludes by showing how to print indexes, find the largest document, use cursors, define aliases, and work with DBRefs.
Node.js is a JavaScript runtime environment that uses Google Chrome's V8 engine. It allows for high concurrency without threads or processes by using an event loop and callbacks for non-blocking I/O. While it can be used for server-side JavaScript applications, its lack of access to the DOM from the server-side presents some drawbacks compared to traditional client-side JavaScript. Overall, Node.js enables highly scalable applications but its non-blocking nature requires some adjustment for developers accustomed to blocking I/O models.
The Stack Exchange infrastructure supports 560 million page views and 34TB of data transferred per month across 1665 requests per second on average. To ensure high performance, Stack Exchange uses load balancers, web servers, caching, and databases in a redundant configuration. Careful performance monitoring and optimization has resulted in homepage and question page render times of 52ms and 33ms respectively.
Ryuji Tamagawa gave a presentation on using MongoDB. He introduced MongoDB as a hybrid of NoSQL and SQL that scales easily. To improve performance on AWS, one must understand MongoDB's memory management, the application's workload pattern, and the size of "hot" data that is frequently accessed. MongoDB does not manage memory itself, instead using memory mapping to leverage the OS buffer. It is important to give the OS enough memory to store hot data and account for indexes. Replication can be used to distribute data across multiple instances for high availability. Performance tests showed SSD-backed instance types had faster write times than non-SSD types for storing Wikipedia data in MongoDB.
This talk will cover lessons learned at Community Engine regarding MongoDB, including: why we moved away from an Hybrid solution using SQL and MongoDB; an outline of the technologies and what we learned using MongoDB on Amazon Web Services; the MongoDB C# driver; MongoDB with SOLR for Full Text Search; how we do migration, deployment and more.
This document discusses MongoDB replication, sharding, and aggregation. It explains that replica sets allow for high availability and redundancy through primary-secondary replication across multiple servers. Sharding partitions data by shard key across multiple replica sets to scale databases horizontally. The aggregation framework provides data aggregation capabilities through pipelines of operations like match, project, group, and sort.
Presentation on MongoDB given at the Hadoop DC meetup in October 2009. Some of the slides at the end are extra examples that didn't appear in the talk, but might be of interest.
Vlad zelinschi optimizing the critical rendering pathCodecamp Romania
ย
The document discusses optimizing the critical rendering path (CRP) of a web page. The CRP refers to the steps between receiving HTML, CSS, and JavaScript and rendering pixels on the screen. These steps include parsing HTML to build the DOM tree, parsing CSS to build the CSSOM tree, combining them into a render tree, running layout to compute geometry, and painting to the screen. Optimizing the CRP means minimizing the time spent in these steps. Some tips include getting CSS to the client fast, eliminating blocking JavaScript from the CRP, and focusing on above-the-fold content. Tools like critical CSS extraction can help optimize the CRP.
Porting ASP.NET applications to Windows AzureGunnar Peipman
ย
Hosting applications on Windows Azure is simple but there are things to change when cloud-enabling existing web applications because cloud is conceptually different than on-premises or shared hosting environment. This sessions goes through main issues one will face when moving applications to cloud. Real-life examples provide elegant solutions to problems and through demos the audience will see how to deploy applications to cloud and how to test and run cloud and hybrid applications on your development machine.
This document discusses remodel, an ORM that maps Ruby objects to Redis to provide fast and scalable data storage. It highlights that remodel is faster than MySQL for read and write operations since it stores data in memory instead of disk. The document demonstrates remodel's features like associations and basic validations and notes its current alpha status and roadmap for improvements.
AJAX allows for asynchronous data retrieval and dynamic display. It uses technologies like XML, XSLT, DOM, and JavaScript. Servlet 3.0 includes annotations and methods to support asynchronous processing, allowing requests to be processed asynchronously without blocking the original thread. The AsyncContext class provides an execution context for asynchronous operations and wraps the request and response.
The document discusses factors that affect website performance, including front-end elements like CSS, JavaScript, images, and back-end elements like caching, threading, and database queries. It notes that only 10-20% of response time is spent on downloading HTML, so focus should be on optimizing other parts of the page load. It also outlines the anatomy of an HTTP request and lists 14 rules for improving performance, such as reducing HTTP requests, using content delivery networks, gzipping components, and making AJAX cacheable. It emphasizes that teams should regularly audit performance and prioritize optimizations.
This document provides an agenda for a presentation on MongoDB. It introduces MongoDB as a popular open-source NoSQL database that uses a document-oriented data model with dynamic schemas like JSON. The presentation will cover NoSQL concepts, MongoDB fundamentals including BSON and examples, and include a hands-on section working with MongoDB. It is aimed at developers interested in learning about using MongoDB for data storage.
This document provides an overview of Bower, a package manager for the web. It discusses the requirements to use Bower, how to install and configure it, and how to run Bower to install dependencies. Bower is used to manage front-end components and their dependencies. It requires Node.js and NPM to be installed first. Then Bower can be installed globally and configured via a bower.json file to specify packages and dependencies. Running Bower will install all dependencies to the default or specified directory. The document also briefly explains how Bower can be used with XPages projects to manage front-end libraries.
When someone wants to learn about Microservice, s/he can easily get lost in the jungle of buzzwords. Specially the relationship between Domain Design, Service to Service communication and Devops are used very frequently in Microservice. But which is what and how are they fit together?
I tried to discuss them in my presentation.
Video can be found here: https://www.youtube.com/playlist?list=PLEYpvDF6qy8YyX2dQX93C88mQ5alaWFXJ
This document provides an introduction to the MEAN stack for beginners. It discusses JavaScript standards and Node.js for the backend using Express.js. It also covers MongoDB as a NoSQL database and its advantages over relational databases. Finally, it discusses Angular as a frontend framework for building single page applications, its core concepts and advantages over other frameworks. The document aims to give beginners an overview of each technology that makes up the MEAN stack.
A talk given at the Infrastructure Coders Meetup in Canberra May 2018.
This presentation gives an overview of the Hyperledger projects in general and some closer look at Hyperledger Fabric and how to deploy it to AWS.
Two deployment options are explored: AWS Blockchain Template and Hyperledger Cello Ansible Agent.
Progressive Web Apps Nedir? JavaScript Service Workers Nedir?Mehmet Seven
ย
Service workers allow web applications to work offline by intercepting network requests and serving cached responses. They load in the background and can handle fetch events even when the web page or browser tab is closed. Service workers enable features like push notifications, background syncing, and caching of pages and files to improve performance and user experience for progressive web apps.
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage EngineMongoDB
ย
An Update on MongoDB's WiredTiger Storage Engine
Keith Bostic, Senior Staff Engineer, MongoDB
MongoDB Evenings Boston
Brightcove Offices
September 29, 2016
This document summarizes a presentation about MongoDB given by Sean Laurent of StudyBlue, Inc. It introduces MongoDB and its features, including its document-oriented data model, flexible schemas, querying and updating capabilities, indexing, drivers, replication and sharding for scalability. Useful MongoDB tools are also discussed like the mongo shell, mongostat, mongotop and MMS monitoring. The document concludes with MongoDB's strengths like horizontal scaling and rapidly evolving schemas, and weaknesses like not being a drop-in replacement for SQL and limitations around transactions.
This document provides an overview and introduction to MongoDB. It discusses what MongoDB is, its features such as being schemaless and document-oriented, and how to install MongoDB. It also covers JSON and BSON formats and compares MongoDB to traditional RDBMS systems. The document recommends MongoDB for non-transactional applications and warns against using it for highly transactional or SQL-required problems.
The document discusses using the MongoDB shell for debugging, testing, and administration tasks. It notes some limitations of using JavaScript in the shell, such as number and date handling. It provides examples of common shell commands like insert, update, remove, loading scripts, running commands, and profiling. Useful shell functions are also demonstrated like printjson and forEach. The document concludes by showing how to print indexes, find the largest document, use cursors, define aliases, and work with DBRefs.
MongoDB is a document-oriented NoSQL database that stores data as JSON-like documents. It is schema-less, scales easily, supports dynamic queries on documents, and stores data in BSON format. MongoDB is good for high write loads, high availability, large and changing datasets. Installation is simple, and it supports replication and sharding for availability and scaling. Data can be embedded or referenced between documents. Indexes and text search are supported. Programming involves JavaScript and MongoDB methods.
Christian Kvalheim gave an introduction to NoSQL and MongoDB. Some key points:
1) MongoDB is a scalable, high-performance, open source NoSQL database that uses a document-oriented model.
2) It supports indexing, replication, auto-sharding for horizontal scaling, and querying.
3) Documents are stored in JSON-like records which can contain various data types including nested objects and arrays.
This document provides an overview of MongoDB, including what it is, its key features of high performance, high availability, and automatic scaling. It discusses MongoDB's use of embedded documents and references to represent relationships between data. The document compares MongoDB to relational databases, noting MongoDB does not require data normalization. It provides examples of how data can be embedded or referenced in MongoDB and when each approach is best.
Schema design with MongoDB (Dwight Merriman)MongoSF
ย
This document discusses schema design considerations for MongoDB, a document-oriented database. It recommends embedding related data rather than linking when possible to facilitate queries and atomicity. It also discusses using compare-and-swap operations to update documents atomically. Indexes should be used to make queries fast. Collections may need to be sharded, requiring the shard key to be chosen carefully. Multiple collections can model more complex data when natural.
This document provides an introduction to MongoDB, including when to use and not use MongoDB, features of MongoDB like document structure, indexing, replication, sharding, and architecture. It outlines the basic MongoDB scheme including databases, collections, and documents. It describes concepts like replication, auto-sharding, and the logical and physical architecture of MongoDB. Finally, it provides steps for initial sharding configuration and backup recommendations.
The document discusses MongoDB, a document-oriented, schema-free database that is built for performance and scalability. It provides examples of inserting, querying, and updating documents using operators. It also lists MongoDB tools like MongoMapper and Mongoid for Ruby on Rails and recommends ways to get started with MongoDB including trying it in a browser or shell and following blogs and presentations.
An Evening with MongoDB - Orlando: Welcome and KeynoteMongoDB
ย
This document provides an overview of MongoDB and introduces some key concepts. It discusses MongoDB's document-oriented data model and how it differs from relational databases. It also covers features like dynamic schemas, ad-hoc querying, secondary indexing, replication, sharding, and new features in MongoDB version 2.2 like concurrency improvements, tag-aware sharding, and TTL collections.
MongoDB is an open-source, document-oriented database that provides flexible schemas, horizontal scaling, and high performance. It stores data as JSON-like documents with dynamic schemas, making the integration of data easier for developers. MongoDB can be scaled horizontally and supports replication and load balancing for high availability.
NoSQL - MongoDB. Agility, scalability, performance. I am going to talk about the basis of NoSQL and MongoDB. Why some projects requires RDBMs and another NoSQL databases? What are the pros and cons to use NoSQL vs. SQL? How data are stored and transefed in MongoDB? What query language is used? How MongoDB supports high availability and automatic failover with the help of the replication? What is sharding and how it helps to support scalability?. The newest level of the concurrency - collection-level and document-level.
MongoDB is a non-SQL document-oriented database where data is stored in BSON format. It is well-suited for write-intensive applications, geo-spatial queries, flexible schemas where requirements may change, and scaling through sharding. Key advantages include very fast writes, no need for migrations when changing schemas, and built-in support for features like sharding, geospatial indexing, and logging to capped collections.
Ryan Angilly is a senior developer at MyPunchbowl.com who has an electrical engineering background but has primarily built web applications using Ruby and Rails with SQL databases. He had no experience with NoSQL or MongoDB until September 2009 when MyPunchbowl decided to explore using it to handle their large datasets from millions of users, events, invites and vendors. He aims to provide a beginner's perspective on transitioning from SQL to MongoDB.
MongoDB is a cross-platform document-oriented database that provides high performance, high availability, and easy scalability. It uses a document-based data model where data is stored in JSON-like documents within collections, instead of using tables with rows as in relational databases. MongoDB can be scaled horizontally and supports replication and sharding. It also supports dynamic queries on documents using a document-based query language.
This document provides information about using MongoDB with Ruby. It discusses installing MongoDB on Mac OS X and Linux, running MongoDB, comparing MongoDB and CouchDB, using MongoDB ORMs like MongoMapper in Ruby applications, defining models and relationships, and additional features of MongoDB and MongoMapper. The conclusion recommends considering MongoDB as an alternative to MySQL for some web applications due to its speed, features, and schema-less flexibility.
The document discusses different types of information retrieval systems such as traditional query-based systems, text categorization systems, text routing systems, and text filtering systems. It also describes some common techniques used in information retrieval systems like inverted indexing, stopword removal, stemming, and vector space models. Finally, it discusses opportunities for integrating information retrieval techniques with natural language processing to develop more accurate and effective retrieval systems.
Brendan McAdams explores the deeper relationship between the MongoDB database and various languages on the Java Virtual Machine such as Java, Scala, Clojure, JRuby and Python as well as the challenges posted getting MongoDB to play nice with these tools and their syntax. Also examined will be frameworks and integration points popular between MongoDB and the JVM such as Spring Data, Morphia and Liftโs MongoDB-Record component
This document discusses MongoDB and provides information on why it is useful, how it works, and best practices. Specifically, it notes that MongoDB is a noSQL database that is easy to use, scalable, and supports high performance and availability. It is well-suited for flexible schemas, embedded documents, and complex relationships. The document also covers topics like BSON, CRUD operations, indexing, map reduce, transactions, replication, and sharding in MongoDB.
This document provides an introduction and agenda for a presentation on MongoDB 2.4 and Spring Data. The presentation will include a quick introduction to NoSQL and MongoDB, an overview of Spring Data's MongoDB support including configuration, templates, repositories and queries, and details on metadata mapping, aggregation functions, GridFS file storage and indexes in MongoDB.
This document discusses MongoDB and how to use it with C#. It provides an overview of why MongoDB is a good fit for web projects, how it compares to relational databases, and how to connect, query, and work with documents using the official C# driver. Code examples and tutorials are referenced to help get started with MongoDB and C# development. Key topics covered include using MongoDB collections, the BSON format, indexing for performance, and embedding vs linking documents.
This document discusses MongoDB and scaling strategies when using MongoDB. It begins with an overview of MongoDB's architecture, data model, and operations. It then describes some early performance issues encountered with MongoDB including issues with durability settings, queries locking servers, and updates moving documents. The document recommends strategies for scaling such as adding more RAM, partitioning data through sharding, and monitoring replication delay closely for disaster recovery.
- MongoDB is a document-oriented, non-relational database that uses JSON-like documents with dynamic schemas, horizontal scaling with sharding and replication, and high performance.
- It is used by many large companies and is a good fit for huge, unstructured data or when dynamic schemas are needed. However, it does not support transactions or have the same data integrity features as relational databases.
- MongoDB can store data in flexible document formats, allows ad hoc queries, and supports common operations like insert, update, delete. Features include replication, sharding, indexing, geospatial queries and MapReduce.
This document provides an overview of developing cloud applications with NodeJS. It discusses using NodeJS with AWS EC2 and MongoDB for the development stack. Popular NodeJS libraries like ExpressJS are mentioned. CoffeeScript is highlighted for writing less code. MongoDB is covered for its document-based and scalable features. Tools like Git, Sublime Text 2, Grunt, and Jenkins are presented for version control, coding, automation, and continuous integration. Lastly, it notes how server and mobile developers can cooperate by dividing work and designing APIs.
- Steve Storey is a hobby coder and professional application architect at MOO, a London-based online printing company.
- MOO's technology stack currently uses a LAMP stack on Debian, but CouchDB is being evaluated as a potential NoSQL option due to its document-based data model and RESTful HTTP interface.
- CouchDB is a document store that allows developer-defined views on documents using map-reduce functions. It has built-in fault tolerant replication and a REST API, making it suitable for storing hierarchical and schema-less data like MOO uses.
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.
Solr cloud the 'search first' nosql database extended deep divelucenerevolution
ย
Presented by Mark Miller, Software Engineer, Cloudera
As the NoSQL ecosystem looks to integrate great search, great search is naturally beginning to expose many NoSQL features. Will these Goliath's collide? Or will they remain specialized while intermingling โ two sides of the same coin.
Come learn about where SolrCloud fits into the NoSQL landscape. What can it do? What will it do? And how will the big data, NoSQL, Search ecosystem evolve. If you are interested in Big Data, NoSQL, distributed systems, CAP theorem and other hype filled terms, than this talk may be for you.
- MongoDB is well-suited for systems of engagement that have demanding real-time requirements, diverse and mixed data sets, massive concurrency, global deployment, and no downtime tolerance.
- It performs well for workloads with mixed reads, writes, and updates and scales horizontally on demand. However, it is less suited for analytical workloads, data warehousing, business intelligence, or transaction processing workloads.
- MongoDB shines for use cases involving single views of data, mobile and geospatial applications, real-time analytics, catalogs, personalization, content management, and log aggregation. It is less optimal for workloads requiring joins, full collection scans, high-latency writes, or five nines u
MongoDB Days UK: Using MongoDB to Build a Fast and Scalable Content Repositor...MongoDB
ย
Presented by Alain Escaffre, Director of Product Management, Nuxeo
Experience level: Beginner
MongoDB can be used in the Nuxeo Platform as a replacement for traditional SQL databases. Nuxeo's content repository, which is the cornerstone of this open source software platform, can now completely rely on MongoDB for data storage. This presentation will explain the motivation for using MongoDB and will discuss different implementation strategies. In this session, you will learn more about the migrations to MongoDB and how we were able to achieve increased performance gains.
TDD a REST API With Node.js and MongoDBValeri Karpov
ย
This document discusses developing and testing a MongoDB and Node.js REST API. It introduces MongoDB and Node.js, and then covers building an API with the following parts: using Mongoose to define schemas for products, categories, and users; building routes with Express; and testing with Mocha and Superagent. Key topics include schema design principles, building RESTful routes, and testing the API end-to-end. The goal is to learn how to structure APIs on MongoDB with Node.js and ensure quality with testing.
Reuven Lerner's first talk from Open Ruby Day, at Hi-Tech College in Herzliya, Israel, on June 27th 2010. An overview of what makes Rails a powerful framework for Web development -- what attracted Reuven to it, what are the components that most speak to him, and why others should consider Rails for their Web applications.
Sigit Kurniawan discusses MongoDB and provides an overview of key concepts. The document covers SQL vs NoSQL, MongoDB features, data types, installation on Windows, and CRUD operations. MongoDB is a document database designed for scalability and flexible schemas. It uses dynamic schemas and is horizontally scalable.
The document discusses NoSQL technologies including Cassandra, MongoDB, and ElasticSearch. It provides an overview of each technology, describing their data models, key features, and comparing them. Example documents and queries are shown for MongoDB and ElasticSearch. Popular use cases for each are also listed.
This document discusses new capabilities in CFEngine 3, an advanced configuration management system. Key points include:
- CFEngine 3 is declarative, ensures desired state is reached through convergence, is lightweight using 3-6MB of memory, and can run continuously to check configurations every 5 minutes.
- It supports both new platforms like ARM boards and older systems like Solaris.
- Recent additions allow managing resources like SQL databases, XML files, and virtual machines in a code-free manner using the Design Center.
- CFEngine treats all resources like files, processes, and VMs as maintainable and ensures they self-correct through convergence to the desired state.
Slide deck for my presentation at MongoSF 2012 in May: http://www.10gen.com/presentations/mongosf-2012/mongodb-new-aggregation-framework .
Kuyper Hoffmann's presentation from the #lspe "Private Clouds" event: http://www.meetup.com/SF-Bay-Area-Large-Scale-Production-Engineering/events/48901162/
The document discusses MongoDB's new aggregation framework, which provides a declarative pipeline for performing data aggregation operations on complex documents. The framework allows users to describe a chain of operations without writing JavaScript. It will offer high-performance operators like $match, $project, $unwind, $group, $sort, and computed expressions to reshape and analyze document data without the overhead of JavaScript. The aggregation framework is nearing release and will support sharding by forwarding pipeline operations to shards and combining results.
Replication in MongoDB allows for high availability and scaling of reads. A replica set consists of at least three mongod servers, with one primary and one or more secondaries that replicate from the primary. Writes go to the primary while reads can be distributed to secondaries for scaling. Replica sets are configured and managed through shell helpers, and maintain consistency through an oplog and elections when the primary is unavailable.
Architecting a Scale Out Cloud Storage SolutionChris Westin
ย
Mark Skinner's presentation to #lspe at http://www.meetup.com/SF-Bay-Area-Large-Scale-Production-Engineering/events/15481232/
Mohan Srinivasan's presentation to #lspe at http://www.meetup.com/SF-Bay-Area-Large-Scale-Production-Engineering/events/15481232/
Mike Lindsey's presentation for The Return of Not Nagios http://www.meetup.com/SF-Bay-Area-Large-Scale-Production-Engineering/events/15481175/
Replication in MongoDB allows for high availability and scaling of reads. A replica set consists of at least three mongod servers, with one primary and one or more secondaries that replicate from the primary. The primary applies all write operations to its oplog, which is then replicated to the secondaries. If the primary fails, a new primary is elected from the remaining secondaries. Administrative commands help monitor and manage the replica set configuration.
Presentation to the SVForum Architecture and Platform SIG meetup http://www.meetup.com/SVForum-SoftwareArchitecture-PlatformSIG/events/20823081/
Vladimir Vuksan's presentation on Ganglia at the "Not Nagios" episode of The Bay Area Large-Scale Production Engineering meetup: http://www.meetup.com/SF-Bay-Area-Large-Scale-Production-Engineering/events/15481164/
This document discusses MongoDB's new aggregation framework, which provides a more performant and declarative way to perform data aggregation tasks compared to MapReduce. The framework includes pipeline operations like $match, $project, and $group that allow filtering, reshaping, and grouping documents. It also features an expression language for computed fields. The initial release will support aggregation pipelines and sharding, with future plans to add more operations and expressions.
AI Changes Everything โ Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
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Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
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At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Hands On: Create a Lightning Aura Component with force:RecordDataLynda Kane
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Slide Deck from the 3/26/2020 virtual meeting of the Cleveland Developer Group presentation on creating a Lightning Aura Component using force:RecordData.
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
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The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
Rock, Paper, Scissors: An Apex Map Learning JourneyLynda Kane
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Slide Deck from Presentations to WITDevs (April 2021) and Cleveland Developer Group (6/28/2023) on using Rock, Paper, Scissors to learn the Map construct in Salesforce Apex development.
Learn the Basics of Agile Development: Your Step-by-Step GuideMarcel David
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New to Agile? This step-by-step guide is your perfect starting point. "Learn the Basics of Agile Development" simplifies complex concepts, providing you with a clear understanding of how Agile can improve software development and project management. Discover the benefits of iterative work, team collaboration, and flexible planning.
Automation Hour 1/28/2022: Capture User Feedback from AnywhereLynda Kane
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Slide Deck from Automation Hour 1/28/2022 presentation Capture User Feedback from Anywhere presenting setting up a Custom Object and Flow to collection User Feedback in Dynamic Pages and schedule a report to act on that feedback regularly.
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
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Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Enhancing ICU Intelligence: How Our Functional Testing Enabled a Healthcare I...Impelsys Inc.
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Impelsys provided a robust testing solution, leveraging a risk-based and requirement-mapped approach to validate ICU Connect and CritiXpert. A well-defined test suite was developed to assess data communication, clinical data collection, transformation, and visualization across integrated devices.
How Can I use the AI Hype in my Business Context?Daniel Lehner
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๐๐จ ๐ผ๐ ๐๐ช๐จ๐ฉ ๐๐ฎ๐ฅ๐? ๐๐ง ๐๐จ ๐๐ฉ ๐ฉ๐๐ ๐๐๐ข๐ ๐๐๐๐ฃ๐๐๐ง ๐ฎ๐ค๐ช๐ง ๐๐ช๐จ๐๐ฃ๐๐จ๐จ ๐ฃ๐๐๐๐จ?
Everyoneโs talking about AI but is anyone really using it to create real value?
Most companies want to leverage AI. Few know ๐ต๐ผ๐.
โ What exactly should you ask to find real AI opportunities?
โ Which AI techniques actually fit your business?
โ Is your data even ready for AI?
If youโre not sure, youโre not alone. This is a condensed version of the slides I presented at a Linkedin webinar for Tecnovy on 28.04.2025.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
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Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
๐ Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
๐ Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
2. What is MongoDB?
โข One of the new breed of non-relational
(โNoSQLโ) databases
โข A document store
โข Instead of flat records (sets of scalars), stores
JSON documents
โข Scalars
โข Array-valued fields
โข Document-valued fields
โข Open source
3. Why MongoDB?
โข Availability
โข Easy replication
โข In principle, similar to MySQL master-slave
โข Automated failover
โข Failure of the โprimaryโ (current master) is detected,
and a โsecondaryโ (slave) is selected and takes
over automatically
4. Why MongoDB?
โข Scalability
โข Easy replication
โข Scale reads by permitting reads from secondaries
โข Built-in sharding
โข Scale writes by spreading load across multiple
shards โ each is a replica set
โข Shards can be added or removed at will
โข No penalty for guessing wrong at start
โข System automatically re-balances shards if they
grow disproportionately
5. Why MongoDB?
โข Simplicity
โข Simple configuration
โข Very few startup parameters
โข Flexible document model
โข Structured data
โข Doesnโt force unnecessary normalization
โข Natural-looking language bindings
โข Client drivers use native language constructions to
represent documents
6. MongoDB is not an RDBMS
โข Sacrifices made for horizontal scalability
โข Eventual Consistency
โข Secondaries are not replicas maintained by
distributed transactions
โข No transactions
โข No joins
โข No SQL
โข Simpler QBE-style query language
7. Where does MongoDB Run?
โข Designed for commodity hardware
โข Can run on O&O infrastructure or in cloud
environments
โข Runs on Windows and most flavors of linux
โข OSX works, but is not recommended for
production
8. Where can I find out more?
โข Tutorials
โข http://try.mongodb.org
โข http://openmymind.net/2011/3/28/The-Little-MongoDB-
Book/
โข Documentation wiki
โข http://www.mongodb.org/
โข mongodb-user on Google groups
โข http://groups.google.com/group/mongodb-user
โข 10gen
โข http://www.10gen.com/
โข Presentations, webinars
โข http://www.10gen.com/what-is-mongodb
โข Support, training, consulting