MongoDB Vs MySQL | Know Their Differences and Which Should You Learn?
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MongoDB Vs MySQL | Know Their Differences and Which Should You Learn?

Last updated on 25th Dec 2021, Blog, General

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Neel Patel (MongoDB Manager )

Neel Patel is a MongoDB Manager for the Respective Industry and has 6+ years of experience working on JavaScript, HTML, CSS, Ajax, jQuery, MongoDB, ReactJS, and VueJS. His articles help to impart knowledge and skills in core fields and give insightful knowledge to students.

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MongoDB represents data as of JSON documents whereas MySQL represents data in tables and rows. MongoDB doesn’t support JOIN but MySQL supports JOIN operations. MongoDB uses JavaScript as query language while MySQL uses the Structured Query Language (SQL).

    • What is MongoDB?
    • What is MySQL?
    • Why Use MongoDB?
    • Why use MySQL?
    • Features of MongoDB
    • Features of MYSQL
    • Difference between MongoDB and MySQL
    • Disadvantage of using MongoDB
    • When to Use MongoDB vs MySQL
    • MongoDB vs MySQL User-Friendliness
    • MongoDB vs MySQL Performance
    • MongoDB vs MySQL Flexibility
    • MongoDB vs MySQL Security
    • Conclusion

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      What is MongoDB?

      MongoDB is a document-oriented NoSQL database used for high volume data storage. MongoDB is a database that came out in the mid-2000s. It falls under the category of NoSQL databases. This type of DBMS uses dynamic schema which means you can create records without first defining the structure, such as fields or types and their values. MongoDB allows you to change the structure of records, which we call documents, by adding new fields or deleting existing ones.

      What is MySQL?

    • MYSQL is a popular and widely used DBMS system. The name is derived from a girl named Mai, the daughter of co-founder Michael Widenius. The source code for MYSQL is available under the GNU GPL. The project is owned and maintained by Oracle Corporation.

    • It is an RDBMS (Relational Database Management System) and mainly works on relational database models. It makes database administration easier and more flexible.

    • In MySQL, you need to pre-define your database schema based on your needs and set up rules that help you control the relationships between fields in your tables.

      Why Use MongoDB?

      Here are the main reasons to use MongoDB:

    • MongoDB is very flexible and adaptable to real business world situations and requirements.
    • Queries can be made to return certain fields within documents.
    • MongoDB supports fields, range-based queries, regular expressions, etc. to search data from stored data.
    • MongoDB is a very simple DBMS system that can easily scale up or down.
    • MongoDB helps you to use internal memory to store working temporary dataset for which it is very fast.
    • MongoDB provides primary and secondary indexes on any field.
    • MongoDB supports replication of databases.
    • You can use MongoDB as a file storage system known as GridFS.
    • MongoDB provides various methods to perform aggregation operations on data such as aggregation pipeline, map-reduce or single objective aggregation command.
    • MongoDB allows you to store any type of file that can be of any size without affecting our stack
    • MongoDB basically uses JavaScript objects in place of procedures.
    • MongoDB supports special collection types like TTL (Time-to-Live) for storing data that will expire at a certain time
    • The dynamic database schema used in MongoDB is called JSON
    • Indexes can be created to improve the performance of searches within MongoDB. Any field in a MongoDB document can be indexed.
    • Replication – Can provide high availability with MongoDB replica sets
    • MongoDB can run on multiple servers, balancing load and/or duplicate data to keep the system up and running in case of hardware failure.

      Why use MySQL?

      Here are some important reasons to use MYSQL:

    • It supports offload reporting, geographic data distribution, etc.
    • Very low overhead with MyISAM storage engine when used for read-most applications
    • Support for in-memory storage engines for frequently used tables
    • Query cache for frequently used statements
    • You can easily learn and troubleshoot MySQL from various sources like blogs, white papers and books.

      Features of MongoDB:

      Here, the important features of MongoDB are:

    • Each database has collections which in turn contain documents.
    • Each document may be different with different fields. The size and content of each document may differ from each other.
    • The document structure of MongoDB depends on how developers build their classes and objects in their respective programming languages.
    • Rows do not require a schema to be defined. Instead, farms can be created on the fly.
    • MongoDB allows you to more easily represent hierarchical relationships, store arrays, and other complex structures.

      Features of MYSQL:

      Here, there is an important feature of MYSQL:

    • MySQL is a community-driven DBMS system.
    • Compatible with various platforms using all major languages and middleware.
    • It provides support for multi-version concurrency control.
    • Compliant with ANSI SQL Standards.
    • Allows log-based and trigger-based replication SSL.
    • Object-oriented and ANSI-SQL2008 compatible.
    • Multilevel design with independent modules.
    • Fully multi-threaded using kernel threads.
    • Available in server embedded DB or client-server model.
    • Provides built-in tools for query analysis and space analysis.
    • It can handle any amount of data up to 50 million rows or more.
    • MySQL runs on many flavours of UNIX and Linux.

      Difference between MongoDB and MySQL:

      Here, are the key differences between MongoDB and MYSQL:

    • In MongoDB, you don’t need to define a schema. Instead, you just drop in documents, not even needing to have identical fields. MySQL requires that you define your tables and columns before storing anything, and each row of the table must have the same number of columns.
    • MongoDB has a predefined structure that can be defined and followed, but at the same time, if you need different documents in a collection, it can have different structures. MySQL uses Structured Query Language (SQL) for database access. You cannot change the schema.
    • Supported languages ​​are C++, C supported languages ​​are C++, C and JavaScript.
    • Ongoing Development MongoDB, Inc. Done through. Continuous development is done by Oracle Corporation.
    • MongoDB supports built-in replication, sharding, and auto-election. MySQL supports master replication and master replication.
    • If no index is found, each document in the collection must be scanned to select documents that match the query statement. If no index is defined, the database engine needs to scan the entire table to find all relevant rows.
    • GPL v2/Commercial Licence Available OD GNU AGPL v3.0/Commercial Licence Available OD.
    • If most of your services are cloud based then MongoDB is best suited for you. If data security is your priority then MYSQL is the best option for you.
    • MongoDB does not impose any restrictions on schema design. MySQL requires that you define your tables and columns before you can store anything. Each row of the table must have the same number of columns.
    • MongoDB uses JavaScript as the query language. MySQL uses Structured Query Language (SQL).
    • MongoDB does not support JOINs. MySQL supports JOIN operations.
    • It has the ability to handle large unstructured data, MySQL is significantly slower than MongoDB when dealing with large databases.
    • Real-time analytics, Content management, Internet of things, Mobile apps Structured data with clear schema.
    • No schema definition is required, therefore less risk of attack due to design, risk of SQL injection attacks.
    • An ideal choice if you have unstructured and/or structured data with potential for rapid growth. A great option if you have structured data and need a traditional relational database.

      Disadvantage of using MongoDB:

    • MongoDB is not a strong ACID (Atomic, Consistency, Isolation and Durability) as compared to many other RDBMS systems.
    • Transactions using MongoDB are complex
    • In MongoDB, there is no provision for stored procedure or functions, so you cannot implement any business logic in database level, which you can do in any RDBMS system.

      Disadvantages of using MySQL

    • Transactions related to system catalogues are not ACID compliant
    • Sometimes a server crash can corrupt the system catalogue
    • Stored procedures are not cacheable
    • MYSQL tables used for PROCEDURES or Triggers are first locked.

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      When to Use MongoDB vs MySQL:

    • The main differences between these two database systems are significant. Choosing which one to use is really a question of approach rather than a purely technical decision.

    • MySQL is a mature relational database system, providing a familiar database environment for experienced IT professionals.

    • MongoDB is a well-established, non-relational database system that offers superior flexibility and horizontal scalability, but at the cost of some of the security features of relational databases, such as referential integrity.

      MongoDB vs MySQL User-Friendliness:

    • MongoDB is an attractive option for developers. Its data storage philosophy is simple and immediately understandable to anyone with programming experience.

    • MongoDB stores data in collections without any applicable schema. This flexible approach to storing data makes it particularly suitable for developers who may not be database experts yet want to use databases to support the development of their applications.

    • Compared to MySQL, this flexibility is a significant advantage: to get the best out of a relational database, you must first understand the principles of normalisation, referential integrity, and relational database design.

    • With the ability to store documents of various schemas, including unstructured data sets, MongoDB provides a flexible developer interface for teams that are building applications that do not require all the security features provided by relational systems. . A common example of such an application is a web application that does not depend on a structured schema; It can easily provide unstructured, semi-structured, or structured data from a single MongoDB collection.

    • MySQL is a common choice for users who have extensive experience using traditional SQL scripting, designing solutions for relational databases, or who are modifying or updating existing applications that are already integrated with a relational system. work. Relational databases may also be a better choice for applications that require very complex but rigid data structures and database schemas involving large numbers of tables.

    • A common example of such a system might be a banking application that requires very strong referential integrity and transactional guarantees to maintain accurate point-in-time integrity of the data.

    • However, it is important to clarify that MongoDB also supports the ACID properties of transactions (atomicity, consistency, isolation, and durability). This enables greater flexibility in building a transactional data model that can scale horizontally in a distributed environment and has no impact on the performance of multi-document transactions.

      MongoDB vs MySQL Performance:

    • It is very difficult to assess the performance of two completely different database systems, as both the management systems perform the task of data storage and retrieval in completely different ways. While it is possible to directly compare two SQL databases with a set of standard SQL benchmarks, achieving the same in non-relational and relational databases is more difficult and subjective.

    • For example: MySQL is optimised for high performance joins on multiple tables that are indexed appropriately. In MongoDB, joins are supported with the $lookup operation, but they are less needed due to the way MongoDB documents are used; They follow a hierarchical data model and keep most of the data in one document, therefore eliminating the need to join multiple documents.

    • MongoDB is also optimised for write performance, and features a specific insertMany() API for fast data insertion, prioritising speed over transaction safety that requires inserting MySQL data row by row. Looking at some of the high-level query behaviours of the two systems, we can see that MySQL is faster at selecting a large number of records, while MongoDB is significantly faster at inserting or updating a large number of records.

      MongoDB vs MySQL Flexibility:

    • This one is easy, and a hands-on win for MongoDB. The schematic design of MongoDB documents makes it extremely easy to build and scale applications over time without the need to run complex and expensive schema migration processes as you would with a relational database.

    • With MongoDB, there are more dynamic options for updating a collection’s schema, such as creating new fields based on the aggregation pipeline or updating nested array fields. This advantage is especially important as databases grow in size. In contrast, larger MySQL databases are slower to migrate schemas and stored procedures that may depend on the updated schema. MongoDB’s flexible design makes this much less of a concern.

    • It’s worth noting that both databases have a lot in common. Both are free to get started, are easy to install on both Linux and Windows, and both have extensive programming language support for popular languages ​​such as Java, Node.js, and Python.

    • In addition, MongoDB offers MongoDB Atlas, a managed cloud solution, that is forever free to use for exploratory purposes, while for the MySQL managed cloud version, you will need an agreement with one of the major public cloud providers. Have to keep an account and come inside them. Free tier conditions for non-payment.

      MongoDB vs MySQL Security:

    • MongoDB leverages the popular role-based access control model with a flexible set of permissions. Users are assigned a role, and that role grants them specific permissions on data sets and database operations. All communications are encrypted with TLS, and it is possible to write encrypted documents to the MongoDB data collection using a master key that is never available to MongoDB, achieving encryption of the data at rest.

    • MySQL supports the same encryption features as MongoDB; Its authentication model is also similar. Users can be given roles, but privileges can also be granted, allowing them to perform particular database operations and against particular data sets.

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    • MongoDB represents data in the form of JSON documents whereas MySQL represents data in tables and rows.
    • In MongoDB, you don’t need to define schema, whereas in MySQL you need to define your own tables and columns
    • MongoDB does not support JOIN but MySQL supports JOIN operations.
    • MongoDB uses JavaScript as the query language while MySQL uses Structured Query Language (SQL).
    • MongoDB is an ideal choice if you have unstructured and/or structured data with potential for rapid growth, whereas MYSQL is a great option if you have structured data and need a traditional relational database.
    • If most of your services are cloud based then MongoDB is best suited for you but if data security is your priority then MYSQL is the best option for you.
    • In this article, we have talked about the main differences between MongoDB and MySQL, which are a schemaless non-relational database system and a relational database system respectively. We have explained when it is better to use one over the other. We’ve discussed the scalability, performance, and user-friendliness for each system. Lastly, we have also explained the flexibility and security features for both the database systems from a comparative point of view.
    • If MongoDB is the right solution for you and you’re currently using MySQL, check out our migration guide. To get started for free, try MongoDB Atlas.

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