Today, in this technology era, new enterprises and companies thinking about to store and manage data in a better way to get vast customer insights. And we can also stick with the new user expectations, or beat competitors market with new business models and applications.
Considering the best DBMS is always a hurdle task in this technology world because too many choices to select from. DBMS classified into two types, i.e. relational and non-relational. In recent years relational Database systems like PostgreSQL, MySQL usage vastly increased.
On the other side, non relational Database management systems like MongoDB. These are able to storing and managing the large volumes of data.
Let us discuss that, which DBMS is best by considering the relational and non- relational DBMS viz.MongoDB and MySQL.
So, let us deep dive into the comparison of MongoDB and MySQL
MySQL is an advanced open source Relational DBMS. It is developed, supported, and distributed by Oracle. MySQL stores and manages data using tables and SQL(structured query language) for accessing the database. SQL language is used in a server called SQL Server Databases.
It uses simple commands such as "INSERT" "DELETE" "UPDATE" "SELECT" to access and manage the data. MySQL allows you to pre-define database schema based on your setup and requirements to oversee the connections between fields and tables.
MongoDB is popularly known as a non relational database system. In MongoDB, the data stored in the form of document format in a binary representation model called BSON. Related information is stored collectively for quick query access by the MongoDB.
In MongoDB, a document is called a big JSON object. Which contains no particular schema or format. For any kind of query access, related data is stored by using MongoDB query language. This process is different for various kind of fields.
If a new type of field requires to be combined with a document, then the field can be generated without altering all other documents in the collection process, without taking the system offline and updating a central system catalog. Essentially, schema validation is used to support data governance handles over each collection.
As we already know that the MySQL follows the relational model database system. In which data is stored in the form of tables. Along with you have to predefined the schema depends on the requirements between fields and tables.
On the other side, in MongoDB data is stored in the form of documents in a collection format. This major difference is a great support to the developers. Because of the code define the schema and there is no need to go with the schema migrations in the future.
Many notions in MongoDB have close analogues in MySQL. The below-mentioned table describes the common connections between MongoDB and MySQL.
MongoDB and MySQL query languages are strong. An unstructured query language used by MongoDB. And the documents stored in the form of big JSON file formats. In the time of the execution process of MongoDB, different types of the operator are used and these are similar to document file JSON. MongoDB supports boolean queries.
On the other side, MySQL works with the structured query language, while accessing the database. Perhaps it is quite simple. This language very strong, and consisting of two parts in it.
DDL (Data Definition Language)
DML(Data Manipulation Language)
Selecting records from the required table for the example:
SELECT * FROM table_name
db.table_name.find()
Inserting records into the required table and is mentioned below:
INSERT INTO table_name (cust_id, branch, status) VALUES ('app1', 'sub', 'C')
$db.table_name.insert({ cust_id: 'app1', branch: 'sub', status: 'C'})
Some of the concepts are mentioned below.
In MySQL, data is dispersed across multiple tables, so at the same time, various tables need to manage to write and read data. Whereas in MongoDB all the documents stored in a single entity called JSON file, this is the reason accessing the data is very fast. This creates to write and read the entire data in a single owned document. Although MySQL supports JSON, but it might not be given the same advantages as MongoDB gives.
MySQL is slow compared to MongoDB because it uses massive volumes of data. When the data volume is greater, it cannot deal with the unstructured language.
Producing applications in MySQL is a slow process because it uses the rigid table structured model. In the same case working with JSON document in MongoDB has vast development cycles by up to 4 to 5 times. MongoDB documents map directly to Oops, so it is easier for developers to visualize and understand how data in application will be merged into the database.
MongoDB can build its control with a variable set of perquisites. And it includes key security features like auditing, authorization, and authentication, etc. It will also support SSL(secure sockets layer) and TLS(transport layer security) to encrypt the server side end. This will make sure that the only required client can elect to access the documents as we encrypted.
Adobe, Electronic Arts, Ebay, Cisco, Google, Facebook, etc. These are the big companies using MongoDB as their database programming language.
Nasa, US Navy, Youtube, Netflix, Spotify, Uber, Bank of America, etc. These are the big companies around the world using MySQL as their database programming language.
MongoDB and MySQL both have their weaknesses and strengths. If you are data need to support legacy application or multi-row transactions, then the relational database is the right option for your enterprise or company. Perhaps, if you need more flexibility and schema-free options, these both can work with unstructured data, in this case, MongoDB is the right and best choice.MongoDB is also called NoSQL database which is more exceptional and suitable for handle more data.
Anjaneyulu Naini loves pursuing excellence through writing and has a passion for technology. He believes in having a skill or talent is more valuable than having just a degree. He is Currently working as a Content writer at MindMajix.com.
Considering the best DBMS is always a hurdle task in this technology world because too many choices to select from. DBMS classified into two types, i.e. relational and non-relational. In recent years relational Database systems like PostgreSQL, MySQL usage vastly increased.
On the other side, non relational Database management systems like MongoDB. These are able to storing and managing the large volumes of data.
Let us discuss that, which DBMS is best by considering the relational and non- relational DBMS viz.MongoDB and MySQL.
So, let us deep dive into the comparison of MongoDB and MySQL
What is MySQL?
MySQL is an advanced open source Relational DBMS. It is developed, supported, and distributed by Oracle. MySQL stores and manages data using tables and SQL(structured query language) for accessing the database. SQL language is used in a server called SQL Server Databases.
It uses simple commands such as "INSERT" "DELETE" "UPDATE" "SELECT" to access and manage the data. MySQL allows you to pre-define database schema based on your setup and requirements to oversee the connections between fields and tables.
What is MongoDB?
MongoDB is popularly known as a non relational database system. In MongoDB, the data stored in the form of document format in a binary representation model called BSON. Related information is stored collectively for quick query access by the MongoDB.
In MongoDB, a document is called a big JSON object. Which contains no particular schema or format. For any kind of query access, related data is stored by using MongoDB query language. This process is different for various kind of fields.
If a new type of field requires to be combined with a document, then the field can be generated without altering all other documents in the collection process, without taking the system offline and updating a central system catalog. Essentially, schema validation is used to support data governance handles over each collection.
Data Storage and Structure
As we already know that the MySQL follows the relational model database system. In which data is stored in the form of tables. Along with you have to predefined the schema depends on the requirements between fields and tables.
On the other side, in MongoDB data is stored in the form of documents in a collection format. This major difference is a great support to the developers. Because of the code define the schema and there is no need to go with the schema migrations in the future.
Terminology Comparison and Concepts
Many notions in MongoDB have close analogues in MySQL. The below-mentioned table describes the common connections between MongoDB and MySQL.
| MongoDB | MySQL |
|---|---|
| Collection | Table |
| Field | Column |
| Aggregation Pipeline | Group_BY |
| Secondary Index | Secondary Index |
| ACID Transactions | ACID Transactions |
Query Language and Syntax Comparison
MongoDB and MySQL query languages are strong. An unstructured query language used by MongoDB. And the documents stored in the form of big JSON file formats. In the time of the execution process of MongoDB, different types of the operator are used and these are similar to document file JSON. MongoDB supports boolean queries.
On the other side, MySQL works with the structured query language, while accessing the database. Perhaps it is quite simple. This language very strong, and consisting of two parts in it.
DDL (Data Definition Language)
DML(Data Manipulation Language)
Selecting records from the required table for the example:
MySQL:
SELECT * FROM table_name
MongoDB:
db.table_name.find()
Inserting records into the required table and is mentioned below:
MySQL:
INSERT INTO table_name (cust_id, branch, status) VALUES ('app1', 'sub', 'C')
MongoDB:
$db.table_name.insert({ cust_id: 'app1', branch: 'sub', status: 'C'})
Some of the concepts are mentioned below.
| SQL Concepts | MongoDB Concepts |
|---|---|
| SELECT | $project |
| LIMIT | $limit |
| join | $lookup |
| ORDER BY | $sort |
| COUNT | $sum |
Performance and Speed
In MySQL, data is dispersed across multiple tables, so at the same time, various tables need to manage to write and read data. Whereas in MongoDB all the documents stored in a single entity called JSON file, this is the reason accessing the data is very fast. This creates to write and read the entire data in a single owned document. Although MySQL supports JSON, but it might not be given the same advantages as MongoDB gives.
MySQL is slow compared to MongoDB because it uses massive volumes of data. When the data volume is greater, it cannot deal with the unstructured language.
Developer Productivity
Producing applications in MySQL is a slow process because it uses the rigid table structured model. In the same case working with JSON document in MongoDB has vast development cycles by up to 4 to 5 times. MongoDB documents map directly to Oops, so it is easier for developers to visualize and understand how data in application will be merged into the database.
Security Model
MongoDB can build its control with a variable set of perquisites. And it includes key security features like auditing, authorization, and authentication, etc. It will also support SSL(secure sockets layer) and TLS(transport layer security) to encrypt the server side end. This will make sure that the only required client can elect to access the documents as we encrypted.
When MongoDB used as Business Application
- Require cloud-based services
- Need to reduce the cost of Schema migration
- Database administrator requirement is less
- shading solutions are required.
Adobe, Electronic Arts, Ebay, Cisco, Google, Facebook, etc. These are the big companies using MongoDB as their database programming language.
When MySQL used as Business Application
- Very Low budget
- Fixed Schema for Databases
- Data Security Priority
- High Transaction rates requirement
Nasa, US Navy, Youtube, Netflix, Spotify, Uber, Bank of America, etc. These are the big companies around the world using MySQL as their database programming language.
Conclusion
MongoDB and MySQL both have their weaknesses and strengths. If you are data need to support legacy application or multi-row transactions, then the relational database is the right option for your enterprise or company. Perhaps, if you need more flexibility and schema-free options, these both can work with unstructured data, in this case, MongoDB is the right and best choice.MongoDB is also called NoSQL database which is more exceptional and suitable for handle more data.
Author Bio
Anjaneyulu Naini loves pursuing excellence through writing and has a passion for technology. He believes in having a skill or talent is more valuable than having just a degree. He is Currently working as a Content writer at MindMajix.com.
awesome blog for mysql vs mongoDB. Hope for more content like this XD
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