MongoDB Developer Training

The latest version of MongoDB is 4.2 that was released on August 13, 2019. The latest minor release version is 4.2.7 that was released on May 26, 2020.

MongoDB Inc. is an American software company that was first established in New York in the year 2007 as 10gen, and the founders of this company are Kevin P. Ryan, Eliot Horowitz, and Dwight Merriman. MongoDB is a NoSQL based open-source database.

MongoDB is an open source database platform which uses JSON like documents and is a NoSQL database program. Here is why you should learn it in 2020: 

• It provides a flexible schema design.
• If you have some commands over JSON, then that knowledge will help you to learn MongoDB easily.
• MongoDB can run over multiple servers and provides load balancing.
• It is open source and hence free to use.
• It is flexible which means you can use new data structures when you want.
• It provides a serverless platform called Stitch that eliminates the need for web hosting and application services.

The intention of the MongoDB Inc. company was to build a completely open-source platform as a service. The company was formerly known as 10gen and the platform it was working on was named Babble, but it didn’t have a great market value. So, both the users and non-users decided to use the database created by the company to use it on its own. The database was named as MongoDB where Mongo is short for the word humongous. MongoDB was released as an open-source database platform in 2009. 

You can get certification and training in MongoDB through MongoDB University. Many companies like Amazon, eBay, Cisco, and Disney are turning to NoSQL databases. Therefore, a certification in MongoDB can help you stand apart from the rest. Currently, the company offers two tracks mentioned below:

Database Administrators or DBAs: They deal with managing MongoDB that includes runtime configurations, sharding, processes, backup, recovery, monitoring, and performance tuning. The target audience includes professionals with some experience in administering in this database environment. Some of the prerequisites include:

• Server application
• Application administration
• CRUD operations
• Sharding
• Indexing
• Basic JAVA programming skills

Database developers: They are developers with knowledge of one or more programming languages. It only has an Associate level credential. The target audience includes software engineers with some professional experience in developing applications built on MongoDB and knowledge of database concepts, JavaScript, and system programming. The topics listed for the developer exam includes:

• CRUD operations
• Sharding
• Aggregation and replication
• Data modelling
• Indexing
• Features and basics of MongoDB

The exams cost $150 each and are conducted online through the company’s proctoring partner, Examity. It is a 90 minutes long exam and there is no penalty for incorrect answers. There are three levels of certifications defined for each role: Associate, Professional, and Master but currently, only the Associate level is available for each role.

MongoDB and SQL vary in the way they handle data.

SQL is a Relational Database Management System language. The data is stored in tables. The SQL Server uses an RDBMS based storage model. It does not provide Agile practices and has a fixed data schema. It has vertical scalability hence increases RAM. SQL provides secondary indexing. It also provides XML support and is licensed hence is not open source. You can merge data from multiple tables using joins, which is not available in MongoDB. SQL supports global transactions. It emphasizes ACID properties, that is, Atomicity, Consistency, Isolation, and Durability.

MongoDB is a non-relational database that supports the JSON query language. It uses MongoDB query language for access. It is faster and more scalable than SQL. It is not a table base rather; it is based on collections and key-value pairs. It does not provide support for foreign keys and triggers. MongoDB provides a dynamic data schema. It has no provision for joins and does not support XML. It is open source, so it is free to use. MongoDB supports Agile practices. It is the best-fit for hierarchical data storage and is horizontally scalable therefore adding more servers. It supports a huge amount of data as compared with SQL. MongoDB is based on CAP theorem that is, Consistency, Availability, and Partition tolerance.

MongoDB is a NoSQL database that stores the database in the form of JSON documents. We start by installing MongoDB on our PC. There are several variants based on development needs. These variants are as follows:

• MongoDB Atlas
• Community server
• MongoDB Enterprise Edition

All three are compatible with every operating system. You must first download the installation files according to your operating system. The installation methods for different operating systems are different. Here, we discuss the installation method in Windows and macOS.

Installation in Windows:

You must download an executable .msi package for installing MongoDB into Windows. Execute the following commands for installation:

> cd /setup-folder/
> msiexec.exe /q /i .msi ^
INSTALLLOCATION=”C:\Program Files\MongoDB\”
ADDLOCAL=”MonitoringTools,ImportExportTools,MiscellaneousTools”

These commands will take you to the specified directory. After installation, you need to configure the default database storage path for MongoDB using the following command:

> md \db\data

Installing in macOS:

Download the .tgz file which contains the necessary binaries. Unarchive the files, you can see a collection of binaries located in the bin folder. Move the bin folder to the required location. Open the directory and change the directory to the bin directory. Execute the following command to create a database in that location:

$ ./mongod --dbpath /path-to-desired-directory/

In this command, you must replace the directory path with the desired path and the server will be started when this command is executed.

Creating the first collection: The data is stored in the form of JSON documents which is collectively termed as collections. These collections are analogous to tables in RDBMS and the documents are analogous to records. In order to create a collection, we must first create a database and connect it to a command line. You need to execute the following command:

$ ./bin/mongo tutorial

This command will connect to the tutorial database and start the database simultaneously. You can notice some lines in the log to specify that the command line is connected to the database.

Execute the following command to create a collection:

$ > db.createCollection(‘Collection Name”);

This creates an empty collection. We will insert data into this collection and perform some operations in this data.

It depends on two factors: the knowledge and skills you already possess and how deep you desire to get into this. If you are a good developer and have some experience in working with similar applications, install MongoDB and start from basics like import/export commands. If you have some hands-on experience with JSON, it will be an added benefit.

There are many resources available online to help you get started with MongoDB.

• Online education courses: KnowledgeHut has launched online classes and they keep on updating it regularly. They offer 20 Hours of Instructor-led Training where you can learn basic to advanced development knowledge of MongoDB features and functionalities.
• You can refer to the following link:  https://www.knowledgehut.com/web-development/mongodb-developer-course
• You can also start with gaining some knowledge in Javascript, later going with C++ and JSON.

MongoDB is one of the top NoSQL databases which has been the most important factor for its popularity. Some of the reasons why MongoDB is so popular are as follows:

1. It is schemaless and hence flexible. It is a document-oriented database that can hold different sizes and types of documents.
2. It is open-source and very easy to install and work with.
3. No complex joins are needed because the data structuring is based on key-value pairs.
4. With the growth of MEAN stack development, MongoDB like databases became more popular since the JavaScript developers can work from the front-end to the database.
5. MongoDB can handle large volumes of data by offering excellent analytics capabilities.
6. It has a very flexible data model and it is very convenient to add or change the fields.
7. It provides an easier way of load balancing.
8. It uses internal memory for storage and hence provides faster access to data.
9. MongoDB has an efficient scale-out architecture.
10. It supports dynamic queries on documents.
11. It is easy to scale.
12. It supports Agile sprints and quicker iteration.
13. MongoDB supports sharding due to which makes it horizontally scalable thus adding more servers.
14. It is the best choice for hierarchical data storage.

MySQL is a Relational Database Management System that stores data in tables, and it uses SQL to access data from the database. On the other hand, MongoDB is a NoSQL database that stores data in the form of JSON documents and it uses MQL (MongoDB Query Language) to access data.

 The main differences between the two are as follows:

• Performance and speed

MongoDB can handle a large amount of unstructured data as compared to MySQL. The flexibility MongoDB offers with JSON documents makes it faster for development processes as compared to rigid rows and columns in MySQL. It makes it easier for the developers to optimize the query performance since the data is stored in a single document and is not distributed over a relational database. Data can be structured within arrays and subdocuments in the same way as data is represented in applications unlike the tabular arrangement of rows and columns in MySQL.

• Schema model

The schema design in MongoDB is very flexible. You can add documents in any collection without establishing any relationship with other documents just by just considering supported data structures. The schema model in MySQL is not dynamic and you need to store data in predefined tables that make it rigid.

• Scalability

MongoDB supports sharding data across multiple nodes which facilitates load balancing. MongoDB is horizontally scalable and hence facilitates adding a greater number of servers. You need not make application-level changes in order to migrate data to larger servers. Whereas, you need to be careful while using JOINs in MySQL in order to distribute data over multiple nodes.

• Higher availability

MongoDB can automatically detect failures in case your database goes down. It elects a new primary node and replaces the malfunctioning node with the new node and normal operation is resumed within a few seconds. This is a manual process in the case of MySQL and therefore takes a longer time. Replication of data in MongoDB makes the data easily available for developers.

• MongoDB is an open-source, non-relational database management system that uses JSON documents to store data whereas PostgreSQL is a relational database management system that stores data in tables and uses both static and dynamic schemas to store and use data.
• If you require to distribute a large volume of data over multiple data, then MongoDB is a better choice since PostgreSQL uses monolithic data architecture.
• In the case of PostgreSQL, you need to predefine the tables, but MongoDB allows you to manage data of any type and structure.
• In MongoDB, data is accessed through documents whereas, in the case of PostgreSQL, data is accessed through rows.

MongoDB is a document-oriented NoSQL database that can handle large volumes of data and is written in C++. The data is stored in JSON-like documents which makes it very flexible as you can add different kinds of fields and structures. The documents can be accessed using key-value pairs. MongoDB offers many features that make it easy to use. The data is stored in documents that are stored in collections. The documents can be of different sizes and different kinds of contents can be added.

MongoDB provides replica sets that ensure higher availability. This also ensures to automatically replace a failed primary replica with a secondary replica. It is highly distributed and provides horizontal scaling thus facilitates adding more servers. It splits data over multiple instances. This is also called sharding and is a very important feature of MongoDB.

MongoDB is an open-source document-based database written in C++ and can handle a large volume of data with a dynamic schema. There are many reasons why MongoDB is a great choice as a database, some of which are as follows:

• Higher data scalability
• Easy data migration
• Rapid iterative development
• Scale-out architecture
• Document-based database that allows variation in the structure and size of documents stored.
• Increased performance since data can be searched and indexed easily in Binary JSON format (BSON).
• MongoDB can be used from a variety of programming languages like C, Java, JavaScript, Perl, Python, .NET, Ruby, Scala, C++, and C#.
• MongoDB supports database transactions.

MongoDB is the best choice when your data is unstructured and complex, and you have a dynamic schema. MongoDB is a good choice for the following applications:

• Blogs and content management.
• Reducing the data migration cost.
• Fast and instant data recovery.
• If most of your services are cloud-based.
• Social networking sites.

MongoDB is easy to learn. The best part is that the company has provided many tutorials on its website. There are a lot of community forums and groups available to discuss your issues. You can also get a certification at a reasonable cost that will help you boost up your profile. The popularity of MongoDB has made it an ideal criterion for recruiters. It is also easy to learn since you can apply your prior knowledge and experience to learn MongoDB. Like, if you are familiar with JSON, you need not learn SQL. Knowledge of programming languages is an added benefit. 

The top features of MongoDB are as follows:

• Aggregation framework
• Document oriented
• Load balancing
• Easy and fast replication
• Data availability
• MongoDB ad-hoc queries
• MongoDB sharding
• Schemaless database
• Dynamic data size and structures
• Supports multiple storages engines
• Geospatial indexing
• Tracking of data services using MongoDB Management Services.