MongoDB Online Training

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MongoDB Training Course

27 hrs. Live Instructor Led MongoDB Training Classes From Easylearning. MongoDB Online Certification and Training course imparts advance skills & knowledge required to become a MongoDB expert.  

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MongoDB in Real World Businesses

There was a time when it took months for planning out an application and its schema but the time has changed now. Especially in this age of big data, constant iteration of our application plays a critical role in satisfying customers. MongoDB enables such iteration. MongoDB data model makes it easy to do such iterations. So developers can easily evolve there applications and the schema follows.

These unique features make MongoDB a very popular database. Because of these features many industries have shifted towards MongoDB and have developed application which were never possible before. 

Here are some case studies showing the charisma of MongoDB in some real world businesses

MetLife is among the largest insurance companies in the world. They wanted to harness there Big Data to create a 360- degree view of its customers so that they could know and interact with its more than 100 million clients as an individual. They spent many years trying to develop a centralized system using relational database but were unsuccessful.

Finally MetLife turned to MongoDB. With MongoDB over just 2 weeks they created a working prototype of a new system and just three months later, they finished a new version of this new system, called “MetLife Wall”.

How MongoDB helped?

MongoDB had this power of the flexible data model. With MongoDB it was easy to evolve schemas in real-time. It stores data in documents therefore managing customer data becomes easy. It can also handle the Big Data quite efficiently with auto sharding and it is also very flexible.

John Bunger, Senior architect at MetLife Said,

“MongoDB helped us to deliver that 360 view of the customer in just 90 days. That was really ground breaking for MetLife, ground breaking for the insurance industry. And it really set an example of the company that we want to be recognized as.”

The weather channel is an American television channel, this channel broadcasts weather forecast, weather related news and analysis. They wanted to develop a mobile application where they could iterate more quickly with a scalable system.

How MongoDB Helped?

With MongoDB, high costs and flexibility was replaced with simplified scale and speed. The weather channel could now quickly distribute the weather alerts to all the subscribers in the affected geographic locations in real-time. The application was now handling more than two million requests per minute with the MongoDB’s capability of scaling out.

Luke Kolin, Vice president of architecture at The Weather Channel said:

“As we work with our user base to figure out killer feature, rapid innovation cycles with MongoDB are a real benefit.”

Expedia is an online travel company. Expedia wanted a new feature of scratchpad because it made the travel search process fast, easy and personalized.

How MongoDB helped?

With MongoDB’s flexible data model and simple horizontal scaling, the users were given a seamless hopping experience and its rich indexes powered analytics that made personalized suggestion to the users while shopping.

Prashanth kokati, senior software engineer at expedia said: “Without MongoDB, it would’ve taken a much bigger team to get the app live so quickly.”

MongoDB is a database that has brought a revolution in the market with its unique features making applications which were never possible before. Hence, all these case studies justifies its popularity.

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MongoDB – The Past

MySQL has been the popular database since around 1995. And de facto it is the world’s most popular database. RDBMS and its SQL language has been an industrial standard database system since 1986. However, there is one drawback of SQL to deal with the real life data.

The need for a new database arises!

Meanwhile, the reliance of unstructured data in every aspect of life was increasing rapidly. With the huge amounts of data due to the advent of internet, the need to have a database to store huge documents was imperative. The initiative of creating a database capable of storing unstructured data began with NoSQL in 1998.  And MongoDB emerged to be one of the NoSQL database types which uses the document oriented approach.

MongoDB came into existence!

MongoDB was created by the founders of DoubleClick – Dwight Merriman, Kevin P Ryan and Eliot Horowitz. They decided to try to create an application stack that would scale out the data easily, as companies everywhere seemed to be running into the same issues.

In fall of 2007, they established 10gen and started working on an application platform for the cloud, which was similar to Google App Engine. The engine’s main language was server-side JavaScript and the scalable database was also JavaScript-y.

Earlier, the appengine was called ed (Eliot and Dwight) and the database was called p (platform). In 2008, the appengine was named Babble and the database as MongoDB. The word MongoDB was originally adapted from the Greek word ‘humungous’. Later it was decided to rip the database out of the app engine and open sourced them. Henceforth, MongoDB started getting users. 

Stability in the production!

In the year 2010, finally the production stable version 1.4 of MongoDB was released and hence became the most sort after database. And in 2013, 10gen announced that it would change its name to MongoDB Inc., associated itself more closely with what ultimately became its flagship product.

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Should College Freshers do MongoDB

MongoDB can be used by everyone, as it is an open-source database. Now a days, everyone is shifting their data from traditional databases to NoSQL databases. MongoDB is one of the most popular NoSQL database in market, with many advanced features and functionalities. Freshers can absolutely go for this new generation database, which is not based on rows and columns instead it stores the data in the form of documents.

Unlike traditional databases, MongoDB provides dynamic schema so there is no need to pre-define any schema. MongoDB is not only free to license but also provides open source environment. It is freely available under the terms of the Free Software Foundation's GNU AGPL Version 3.0 commercial license. And the language drivers are available under an Apache License.

Why should freshers go for MongoDB?

• There are 2000+ jobs found for MongoDB at naukri.com and TIMESJOBS.COM. • Also the downloads for MongoDB are increasing every single month. • MongoDB is a database that provides high performance, high availability, and easy scalability. MongoDB has official drivers for a variety of popular programming languages and development environments. So freshers can integrate MongoDB with any of the programming language with which they are familiar. • Earlier its scope was not in India, as it was not so popular. But now it has emerged in India also, and it has been used by more than 600 customers and other numerous adoptees in India. Now India also has some of the largest MongoDB User Groups in APAC, including Bangalore with 701 users, Delhi with 451 users and Pune with 301 users. 

It’s easy for the freshers to learn MongoDB, as it is very easy to use and learn. It provides much better flexibility and performance than the traditional databases. And it could be used by freshers who are interested in learning a new kind of database, which alone is able to handle the Big Data.

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MongoDB Integration with Other languages

MongoDB Integration with Other languages

MongoDB is an open-source database, which is reliable, globally scalable and inexpensive to operate. MongoDB provides native drivers for all popular programming languages and frameworks to make development natural. A list of supported drivers include:

Java, .NET, Ruby, PHP, JavaScript, node.js, Python, Perl, PHP, Scala etc.

An application communicates with MongoDB by way of a client library, called a driver is used for interacting with MongoDB in a particular language. The popular MongoDB drivers and client libraries include:

PHPMoAdmin is MongoDB Administration tool for PHP built on a stripped down version of the Vork high-performance framework. It can help you discover the source of connection issues between PHP and MongoDB. 

Mongobee is a java tool which can help you manage changes in your MongoDB database and keep them synchronized with your java application. It provides new approach for adding changes based on Java classes and methods with appropriate annotations.

PyMongo is a Python distribution containing tools for working with MongoDB. MongoVUE is a .NET Graphical User Interface that gives an elegant and highly usable interface for working with MongoDB.

Node.js Driver is the officially supported node.js driver for MongoDB. It is written in pure JavaScript and provides a native asynchronous Node.js interface to MongoDB. 

MongoDB also supports some Third-party GUI tools like: Robomongo, Fang of Mongo, Mongo3, UMongo etc. 

Robomongo is a shell-centric cross-platform open source MongoDB management tool. It embeds the same JavaScript engine that powers MongoDB’s mongo shells. Everything you can write in mongo shell, you can write in Robomongo. Robomongo provides you with syntax highlighting, auto-completion, different view modes (text, tree) & more. It has its own features like multiple shells and multiple results. 

Fang of Mongo is a web-based User Interface built with Django and jQuery. UMongo is a cross-platfrom Management-GUI, implemented in java.

MongoDB can be used with many programming languages and development environments as we have discussed above. With MongoDB, you can build applications that were never possible with traditional relational databases, as with the advanced features it provides an extensive driver support with the programming languages.

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Top 5 quotes of MongoDB and NoSQL Industry leaders

MongoDB is the most popular NoSQL next-generation database that already serves many Fortune 500 and Global 500 companies across financial, e-commerce, gaming, healthcare, education and science etc. MongoDB was developed by Dwight Merriman, Eliot Horowitz and Kevin P. Ryan. Eliot Horowitz is the founder and CTO of MongoDB Inc., and Dwight Merriman currently serves as the founder and chairman of MongoDB Inc.

“The development period for MongoDB 3.0 has been the most eventful of my entire career,” said Eliot Horowitz. As MongoDB 3.0 brings with it massive improvements to performance and scalability, enabled by comprehensive improvements in the storage layer and with much more features. Again he says that “Users love MongoDB because it offers the fastest time to value compared to any other DBMS technology”. “With 3.0, MongoDB’s performance, scalability, and manageability now set the standard for today’s most demanding applications. Moreover, with this release users can build applications that deliver between 7x and 10x greater write throughput, while using up to 80 percent less storage, and managing their operations with up to 95 percent less effort.” Eliot Horowitz says that NoSQL databases can handle unstructured data. For ex: “Suppose you want to have a media collection. A person wants to upload pictures, video and anything that pertains to him or her. One big problem is that photos have different attributes than videos. You want to be able to store everything in the same collection but have different indexes for videos and song titles and photos, each with different fields but everything mashed all together. That is a pretty typical use example for what NoSQL databases like MongoDB can do.” “In five short years, the MongoDB community has transformed the data management landscape, creating the first compelling alternative to 40 years of relational databases,” said Max Schireson, CEO of MongoDB. That means that MongoDB has gained high popularity in few years, among other NoSQL databases and the RDBMS systems. “The cost of managing traditional databases is high. Mistakes made during routine maintenance are responsible for 80 percent of application downtime,” said Dev Ittycheria, President and CEO of MongoDB Inc. As it is easy to maintain the MongoDB database, as compared to other Relations databases.

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Friend or Foe: MongoDB vs Hadoop

MongoDB and Hadoop are friends in the sense that we can integrate them via Mortar (platform for doing data science and data engineering at high scale in the cloud).  With your MongoDB data in Hadoop, you can run advanced algorithms and reports on it at scale.

But sometimes they act as foe because In case of Hadoop, the main flaw is that it has a single point of failure, the “NameNode”. If it goes down the entire system becomes unavailable but in case of MongoDB there is no such flaw like single point failure but to solve such problem we have replicated resources.

  What is Hadoop?

  Hadoop is the open source implementation of MapReduce paper which was published by Google to handle the big data for analytical purpose.

  When to use it?

  Hadoop is basically used to process data for Analytical purpose rather than real time processing. Hadoop comes to solve the problem when there is large set of data is involved e.g. hundreds of gigabytes or even hundreds of petabytes of data is involved.

  What is MongoDB?

  MongoDB is an open source database that uses a document oriented data Model. MongoDB is designed for real-time processing. It is a powerful, flexible and scalable general purpose database.

  When to use it?

  It is used to handle the massive amount of data and data processing at a time is done on a small subset of data.

                                                            MongoDB vs Hadoop

  1 .MongoDB is a database and focuses on storage            and efficient retrieval of data.

  1. Hadoop is a data processing and analysis framework and focuses on data processing using MapReduce.

2. MongoDB supports rich Queries like Traditional RDBMS systems and written in a standard JavaScript shell.

2. Hadoop has two different components for writing MapReduce code i.e. PIG (scripting language similar to python, Perl) and HIVE (like SQL language).

3. MongoDB is written in C++ and manage the memory more cost-efficiently.

3. Hadoop’s HBase is written in java and java garbage collection (GC) is there to manage the memory.

4. MongoDB based on the simple authentication and MD5 hash.

  4. Hadoop is based on the fairly rudimentary security in its various framework.

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GridFS-A special feature of MongoDB

MongoDB provides a special specification named GridFS for storing and retrieving files such as images, audio files, video files, etc that exceed the BSON-document size limit of 16MB. It is kind of a file system to store files but its data is stored within MongoDB collections.

GridFS basically divides each file into several parts or chunks, instead of storing the file in a single document and each chunk is stored as a separate document. And the limits for the chunk size is 255k. GridFS uses two collection to store files: • Chunks collection(which stores the binary chunks) • Files collections(store the file’s metadata)

Chunks Collection: In the chunk collection, each document represent the distinct chunk of a file as represented in the GridFS. Following is the example to represent the chunk collection: { “_id” :<objectid>, “Files_id” :<objectid>, “number” :<num>, “data” :<binary> } Files Collection: Each document present in the files Collection represents a file in the GridFS. Following is the example of file collection. {  "_id" : <ObjectId>,  "length" : <num>,  "chunkSize" : <num>,  "upload_Date" : <timestamp>,  "md5" : <hash>,  "file_name" : <string>,  "content_Type" : <string>,  "aliases" : <string array>,  "metadata" : <dataObject>, }

How to add files to the GridFS? Now to store the mp3 file using GridFS using the Put command. For this use the mongofiles.exe utility present in the bin folder of the MongoDB installation folder. Open the command prompt, navigate to the mongofiles.exe in the bin folder of the MongoDB installation folder and type the command: >mongofiles.exe -d GridFS put Song.mp3 Adding an mp3 file to GridFS:

In the chunk collection, each document represent the distinct chunk of a file as represented in the GridFS. Following is the example to represent the chunk collection

To show the mp3 file connect to the mongo server and navigate through the databases, use the gridfs database and execute the find() command inside the fs.files collection. >db.fs.files.find()

Advantages of GridFS:

• Helps to overcome file system limitation like storing large number of files. • For accessing selected portion of the files. • Storing user generated file content • Storing those documents whose size is greater than the 16MB. • Storing the files along with the databases and eradicating the problems like:  Replicating the files to all needed servers  How to delete the copies when the file is deleted? etc.

Conclusion: So GridFS is a very attractive feature of MongoDB which is useful not only for storing files that exceed 16MB but also for storing any files for which the need is to access without having to load the entire file into memory.