Hello World! This is my brand new post and you are cordially welcome. Here we are about to be introduced with ‘MongoDB’.
In SQL database, data stored in relational tabular form where MongoDB is NoSQL database program that provides a mechanism for storage and retrieval of data in documents of tree structured collections.
Before being too much descriptive let’s check out a brief example. Let’s assume we have a data table named persons in SLQ like below image.
In above figure there are four fields in table named person - First name, last name, email and age. If people want to feed the entire field then its fine which is shown in case of John Miller but take a close look on Steve Smith row, he doesn’t want to feed the email ID. In this case the email field is left empty in Steve Smith’s row. Next case of Edmond Woods who also wants to feed his address but there is no field of address is predefined therefore he cannot feed his address. To do so database handler must define an address field in person’s table schema but the problem is that if John Miller and Steve Smith don’t want to feed their address then the address field of their rows will leave empty.
The synopses of the above example that you must predefined the schema of every expected data-field either user fill them or not while working with SQL. This can create lots of null data in your table which occupies small amount of space in your database, even though it is very small but it does.
Now let’s move on and check an example of MongoDB.
Above image is showing the persons collection where the data is stored in the form of JSON-Objects.
You can notice the there is no predefined schema of person’s collection. John Miller is updated all the four fields but take a close look once again on Steve Smith he didn’t update the email ID and there is no field is predefined for email. Edmond Woods who updated the address but there is no field named address is defined for John Miller and Steve Smith.
This feature of MongoDB (NoSQL) database make it extreme flexible and worthy. The distributed systems design allows you to intelligently put data where you want it and supports a wide variety of data and queries. It avoids creating useless null data into database.
MongoDB grow horizontally through native sharding. A database shard is a horizontal partition of data in a database. Each individual partition is referred to as a shard or database shard. Each shard is held on a separate database server instance, to spread load. This feature allows scaling the database easily.
It is essential to compare SQL and MongoDB to understand the basic architecture and functionality of the MongoDB (NoSQL) database. Now we have a brief understanding of MongoDB database. To work with MongoDB you must have command over the JavaScript language, especially JavaScript Object and JavaScript Object Notation (JSON).
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What is MongoDB?
MongoDB is a general purpose, cross-platform, document-oriented distributed database program with the high flexibility and easy scalability. Unlike SQL MongoDB stores data in JSON like documents with flexibility. The term ‘flexibility’ is used here which means you are not bound to a fixed data field structure or predefined database schema. Field can be differing from document to document. Mongo DB works on the concept of collections and documents.In SQL database, data stored in relational tabular form where MongoDB is NoSQL database program that provides a mechanism for storage and retrieval of data in documents of tree structured collections.
Before being too much descriptive let’s check out a brief example. Let’s assume we have a data table named persons in SLQ like below image.
In above figure there are four fields in table named person - First name, last name, email and age. If people want to feed the entire field then its fine which is shown in case of John Miller but take a close look on Steve Smith row, he doesn’t want to feed the email ID. In this case the email field is left empty in Steve Smith’s row. Next case of Edmond Woods who also wants to feed his address but there is no field of address is predefined therefore he cannot feed his address. To do so database handler must define an address field in person’s table schema but the problem is that if John Miller and Steve Smith don’t want to feed their address then the address field of their rows will leave empty.
The synopses of the above example that you must predefined the schema of every expected data-field either user fill them or not while working with SQL. This can create lots of null data in your table which occupies small amount of space in your database, even though it is very small but it does.
Now let’s move on and check an example of MongoDB.
Above image is showing the persons collection where the data is stored in the form of JSON-Objects.
You can notice the there is no predefined schema of person’s collection. John Miller is updated all the four fields but take a close look once again on Steve Smith he didn’t update the email ID and there is no field is predefined for email. Edmond Woods who updated the address but there is no field named address is defined for John Miller and Steve Smith.
This feature of MongoDB (NoSQL) database make it extreme flexible and worthy. The distributed systems design allows you to intelligently put data where you want it and supports a wide variety of data and queries. It avoids creating useless null data into database.
MongoDB grow horizontally through native sharding. A database shard is a horizontal partition of data in a database. Each individual partition is referred to as a shard or database shard. Each shard is held on a separate database server instance, to spread load. This feature allows scaling the database easily.
It is essential to compare SQL and MongoDB to understand the basic architecture and functionality of the MongoDB (NoSQL) database. Now we have a brief understanding of MongoDB database. To work with MongoDB you must have command over the JavaScript language, especially JavaScript Object and JavaScript Object Notation (JSON).
Related Topics
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