SQL is one of the most widely used query language over the databases. But There are certain use case were we cannot Use SQL as Database . As we know SQL is database have fix schema . It is type of relational Database . So sometimes the situation arise were we need the Schema less Environment , In that case we have to use NOSQL . MongoDB is one type of NOSQL .
MongoDB is a document database built on a scale-out architecture that has become popular with developers of all kinds who are building scalable applications using agile methodologies.
MongoDB was built for people who are building internet and business applications who need to evolve quickly and scale elegantly. If you are doing that, we should consider MongoDB.
Instead of storing data in tables of rows or columns like SQL databases, each row in a MongoDB database is a document described in JSON, a formatting language . Document databases are extremely flexible, allowing variations in the structure of documents and allowing storage of documents that are partially complete. One document can have others embedded in it. Fields in a document play the role of columns in a SQL database, and like columns, they can be indexed to increase search performance.
Industry Using MongoDB as Database.
Pebble — Customer Case Study
Pebble is the originator of the smartwatch category, and Pebble Time is the brand’s latest, most innovative product. Featuring Pebble’s new timeline interface, which turns moments you care about — notifications, calendar events, weather, sports scores, breaking news, missed calls, app alerts — into pins that let you see what’s ahead or catch up on what’s already happened. Timeline gives you the info you need, when you want it–so you can live “now” to the fullest. Using Cloud Pebble, developers can build apps to enhance the Pebble smartwatch experience. MongoDB powers the Pebble timeline API, which allows developers to create web-based, time-oriented, near-real time experiences directly on Pebble Time users’ wrists, opening up the Pebble development platform to the open web in completely new ways.
SmartyPal — Customer Case Study
SmartyPal is an educational platform and iPad app based on children’s stories, powered by an intelligent adaptive learning engine. MongoDB is at the heart of SmartyPal, defining the structure and layout of each individual story with its associated games. MongoDB also enables a personalized learning experience based on hundreds of raw data points from each individual’s gameplay, which are analyzed by SmartyPal’s adaptive learning algorithms.
MetLife is a leading global provider of insurance, annuities and employee benefit programs. They serve about 90 million customers and hold leading market positions in the United States, Japan, Latin America, Asia, Europe and the Middle East. MetLife uses MongoDB for “The Wall”, an innovative customer service application that provides a consolidated view of MetLife customers, including policy details and transactions. The Wall is designed to look and function like Facebook and has improved customer satisfaction and call centre productivity. The Wall brings together data from more than 70 legacy systems and merges it into a single record. It runs across six servers in two data centres and presently stores about 24 terabytes of data. MongoDB-based applications are part of a series of Big Data projects that MetLife is working on to transform the company and bring technology, business and customers together.
Shutterfly is a popular internet-based photo sharing and personal publishing company that manages a store of more than 6 billion images with a transaction rate of up to 10,000 operations per second. Shutterfly is one of the companies that transitioned from Oracle to MongoDB.
During the evaluation at the time of transition to MongoDB, it became apparent that a non-relational database would suit the Shutterfly’s data needs better and thereby possibly improving programmer’s productivity as well as performance and scalability.
Shutterfly considered a wide variety of alternate database systems, including Cassandra, CouchDB and BerkeleyDB, before settling on MongoDB. Shutterfly has installed MongoDB for metadata associated with uploaded photos, while for those parts of the application that require richer transactional model, like billing and account management, the traditional RDBMS is still in place.
Till now, Shutterfly is happy with its decision of transitioning to MongoDB and what Kenny Gorman (Data Architect of Shutterfly) has to say about it is, “I am a firm believer in choosing the correct tool for the job, and MongoDB was a nice fit, but not without compromises.”