React JWT Authentication with Axios: Handling Access and Refresh Tokens

 

 

 

   What is Mongo DB?

            Mongo DB is a document-oriented NoSQL database that can hold a lot of data. Instead of tables and rows, Mongo DB employs collections and documents. Mongo DB's fundamental data unit is key-value pairs, which are used to create documents. In the same way that relational database tables include sets of documents and functions, collections do as well.

             Mongo DB is capable of handling a large variety of data types. It's one of a slew of non-relational database systems that have sprung out under the NoSQL banner, most especially for use in big data applications and other processing activities involving data that doesn't fit well into the traditional relational paradigm. Unlike relational databases, Mongo DB's design is based on collections and documents rather than tables and rows.

 

Mongo DB Features

Mongo DB also guarantees high availability, scalability, and adherence to the most demanding data security and privacy requirements. Mongo DB Cloud is a unified data platform that includes a worldwide cloud database, as well as search, data lakes, mobile, and application services.

 

1. Each database consists of collections, which are comprised of documents. Each document is separate, with a different number of fields. The size and content of each document may be different.

2. The document's structure is based on how programmers create classes and objects in various programming languages. 

3. For the rows, there is no need to define a schema (or documents, as they are known in Mongo DB). Instead, fields can be constructed on the fly.

4. Mongo DB's data model simplifies the definition of hierarchical connections, the storage of arrays, and the storage of other more complex structures.

5. Scalability - Mongo DB systems are extremely scalable. Clusters have been defined by companies worldwide, with some running 100 or more nodes and millions of documents in the database.

How Mongo DB works

 

Mongo DB works using records, which are documents that contain a data structure made up of field and value pairs. Mongo DB’s basic data unit is the document. The documents resemble JavaScript Object Notation, although they employ a binary JSON variation (BSON). These documents have fields that are analogous to columns in a relational database. The values contained can be a number of data formats, including other documents, arrays, and arrays of documents. The main key will be used as a unique identifier in documents.

                                               For data consistency, the NoSQL DBMS has a single master architecture, with subsidiary databases serving as backups of the parent database. For automated failover, operations are automatically replicated to those alternative databases. Because it is a NoSQL tool, it does not use the traditional rows and columns associated with relational database administration. It is a collection-based and document-based architecture. A set of key-value pairs is the basic unit of data in this database. It provides for different fields and structures in documents.

{_id:

name: “Navindu”,

Age: 23,

Address: {{street: “192 Dewala street”,

           city: “Makola”,

           state: “Kiribathgoda”,

           zip: “13400”,

           country: “SRILANKA”}}

}

           Mongo DB has a highly elastic data model that allows you to integrate and store data of various forms without sacrificing powerful indexing options, data access, or validation criteria. What this means is that instead of spending extra time preparing data for the database, you can focus on making your data work harder. Mongo DB adds the _id column to uniquely identify each document in the collection.

 

Key Components of Mongo DB Architecture

 

1. _id — Every Mongo DB record must have this field. The _id field in a Mongo DB document represents a unique value. Mongo DB will automatically construct an _id field if you create a new document without one. So, in the case of the preceding customer table, Mongo DB will assign each document in the collection a 24-digit unique number.
2. A collection is a set of documents in Mongo DB. In any other relational database management system (RDMS), such as Oracle or MS SQL, a collection is the equivalent of a table. A collection exists within a single database. As stated in the introduction, collections do not impose any kind of structure.
3. Cursor - A cursor is a pointer to the result set of a query. Iterating through a cursor allows clients to retrieve results.
4. Database - Similar to how a relational database management system (RDMS) is a container for tables, a database is a container for collections. A Mongo DB server can hold many databases. Document - A document is essentially a record in a Mongo DB collection. Field names and values will be found in the document.
5. The abbreviation for JavaScript Object Notation (JSON) is JavaScript Object Notation. This is a simple text format for expressing structured data in a human-readable fashion. 
6. A name-value pair in a document is called a field. In relational databases, fields are similar to columns. A Field with Key-Value Pairs is depicted in the diagram below. In the example below, the Customer ID is one of the key-value pairs defined in the document.

5.     Mongo DB vs. RDBMS:

          You can directly compare Mongo DB NoSQL to RDBMS and map the two systems' different terminologies: The table join is an embedded document, the column is a field, the tuple/row is a document, and the RDBMS table is a Mongo DB collection. The number of tables and the relationships between them is shown in a normal relational database schema, although Mongo DB does not use the idea of a relationship.

Examine the table below to see how a professional NoSQL database like Mongo DB differs from a relational database management system. Nine different analogies between the two have been explained in this blog.

 

       Mongo DB 

• Database that is both document-oriented and non-relational.
• Document-based
• Field-based
• Key-value pair based on a collection
• Provides a JavaScript client for executing queries.
• Setup is relatively simple.
• SQL injection has no effect.

      RDBMS

• Database with a relational structure
• Row-based
• Based on columns
• Based on a table
• Doesn't support querying using JavaScript
• Setup is not as simple as it appears.
• SQL injection is a serious threat

Data integrity is a well-known feature of relational databases. Mongo DB does not have an explicit need for this.

     To avoid orphan records and duplicates, RDBMS demands that data be normalized first. Normalizing data necessitates the creation of more tables, which requires the creation of more table joins, which requires the creation of more keys and indexes. As databases grow in size, performance can become a problem. Again, Mongo DB does not make this a necessity. Mongo DB is adaptable and doesn't require data to be normalized before it can be used.