- MongoDB vs. MySQL: When to Use?
- Mariana Berga
- The Nuggets translation Project
- Permanent link to this article: github.com/xitu/gold-m…
- Translator: samyu2000
- Proofread by: PassionPenguin, Greycodee
Analysis of MongoDB and MySQL usage scenarios
MongoDB and MySQL are both good databases with excellent performance. However, their success depends on the application scenario. The first step is to understand the different operating environments in which they operate, rather than comparing their strengths and weaknesses. Therefore, in this article, we will explore the key features, differences, and advantages of MongoDB and MySQL.
By staying through this article, you’ll have a better understanding of the differences between the two databases (which are quite different) so you can make an appropriate choice.
What is MySQL?
MySQL is an open source RDBMS, or relational database system. More specifically, a relational database system is an application for updating, managing, and designing relational databases, which is useful and conducive to program coding. A relational database is a database (data is usually presented as a table) that supports querying data in the same database based on the relationship between the data. MySQL, PostgreSQL, and SQL are relational database systems that have their own SQL (Structured Query Language) standards.
MySQL, one of the most commonly used open source RDBMS, was introduced in 1995 and continues to be praised by the industry for its reliability. And it’s easy to use. Because the database schema is predefined according to certain rules, data exists in the form of rows and columns, and can also reflect the relationships between fields in different tables.
What is MongoDB?
MongoDB is also open source, but unlike MySQL, it is a file-storage-based database. It stores documents in data sets rather than in relational tables.
With MongoDB, the data schema is not fixed. It is possible to delete or modify certain attributes of a document within a collection, which provides great flexibility. Moreover, documents within the same collection can have completely different structures.
Differences between MongoDB and MySQL
As mentioned earlier, the main difference between the two open source databases is that MySQL is relational and MongoDB is file-based. In this chapter, we’ll examine what this difference represents, including data schema and capacity, performance and speed, security, and query language.
Data schema and capacity
In MongoDB, data exists in the form of name and value pairs similar to JSON files. Due to its schema design, it has fewer constraints on data. So if the data is rapidly changing, MongoDB has an advantage. In addition, MongoDB provides predefined constructs that can be used if needed.
MySQL is different when it comes to data schemas. Schema can be changed in MySQL, but it is less flexible and dynamic than a database based on file storage. MySQL forces a check before any data is stored, and the tables and columns are executed only if the saved data complies with predefined rules. Changing the data schema also requires a redesign of the DDL (Data Definition Language) and DML (Data Modeling Language) of the database.
Both relational and document databases use DDL and DML concepts. However, in relational databases, DDL and DML definitions are important. On the contrary, MongoDB’s data mode is highly extensible and does not focus on data structure as MySQL does. While this may seem like a big disadvantage, this consistency is actually MySQL’s biggest advantage because it ensures that the data is structured and keeps it clean.
Each MongoDB database contains several collections, or more accurately, documents. These documents may contain a wide variety of information fields and types, and support storing data of various contents and sizes. In MySQL, because data schema comparisons are binding, every piece of data in a table has the same column, making it difficult to manage when the database size is large. So, if the database is too large and complex, MySQL is not as powerful as MongoDB.
In other words, MongoDB based on file storage is better suited to handle large amounts of complex data with variable structure than relational MySQL.
Performance and speed
MongoDB receives any data faster than MySQL and can receive more data than MySQL. However, in a business where the volume of data is small and the data structure is not so variable, speed is not necessarily a priority, and other features such as reliability and consistency become a priority.
We need to compare the speed of each database, but more importantly, understand which database is more appropriate or performs better within the constraints of business or project requirements.
If the project needs to focus on data privacy and integrity, MySQL is a mature and reasonable solution. Because the data schema is clear, MySQL systematizes data types with data tables, making the respective values in the data fully searchable and easy to search, so using MySQL means that the database structure is stable. However, it is not suitable for unstructured data. MySQL’s greatest advantage (and arguably its greatest disadvantage) is the need to define data structures beforehand, which avoids a lot of technical debt. In some cases, however, the data is too complex to design an appropriate schema.
MongoDB, on the other hand, is more flexible and faster when dealing with unstructured data. In cases where data schemas are difficult to define in advance, a database based on file storage is suitable. However, if the data is diverse, adding an index to an attribute of the data is difficult to implement. So the data schema needs to be constantly optimized. At this point, if the one-sided pursuit of consistency, but will bring risks.
security
MySQL uses a permission-based security model, that is, users need to be authenticated to perform operations on the database. The system can also grant or prohibit users from performing operations on a database. And if an application needs to get data from a database, it needs to establish an encrypted connection using the secure protocol SSL.
The security system of MongoDB consists of role-based access control, including identity authentication, authorization and auditing. In addition, TLS and SSL are used if encryption is required.
While MongoDB and MySQL both provide security models that can be used in situations where a project requires some degree of reliability and data consistency, MySQL is the most appropriate option.
Characteristics of transactions: atomicity, consistency, isolation, and persistence
In computer science, ACID refers to properties that database transactions should have for data to be valid. They are atomicity, consistency, isolation and persistence.
MySQL is generally considered ACID compliant, but for MongoDB, simply complying with the ACID standard is not an optimal strategy because it compromises speed and availability. MongoDB began supporting ACID multi-document transactions in 2018. By default, however, this option is turned off. On the other hand, MySQL transactions comply with the ACID standard, which ensures data validity in terms of transaction attributes.
The query
MySQL uses SQL statements to fetch data from one or more tables. SQL, the most popular query language, only needs to be combined with DDL and DML to communicate with the database system.
In contrast, MongoDB uses an unstructured query language. When querying data from a JSON-based file database, the first priority is to search for documents using attributes that match the results.
In other words, in order to retrieve data in MongoDB, you need to perform queries. This function should be executed: db.collection.find(). MongoDB supports multiple languages (like Python, Java, C#, Perl, PHP, Ruby, and JavaScript), as long as queries can be built in that language. Composite queries can use query operators to establish specific conditions for individual fields in a collection document. Query operators ($and, $OR, $type, $eq, etc.) are used to define conditions and filters. The data obtained through the query is determined by the query conditions, and further, the query, update, and delete objects are determined by the query conditions.
However, MongoDB does not support join queries and there is no equivalent. MySQL supports the JOIN operator (inner JOIN, outer JOIN, left JOIN, right JOIN, and full JOIN), which is used to retrieve data from two or more tables. Simply put, these operations allow you to associate data in multiple tables using a single SQL statement.
MongoDB vs. MySQL: In what situations are they used
It is difficult to say which database is better because of the different environment. In fact, the operation principle of MySQL and MongoDB is completely different, and both are very useful database management systems. So even if one of these works well for some businesses or projects, it may not be the best choice for other different needs. The company will choose the right database according to different project requirements.
One of the few things they have in common is that they are open source and easy to access. In addition, commercial versions of both systems are available with additional features. Despite these similarities, the key difference between them is that one is relational and the other is not.
MongoDB is a document database and is the most suitable solution for high-volume environments because it does not limit the amount and type of data. MongoDB is well suited for cloud service development because of its level of scalability and flexibility required by cloud services. In addition, it reduces load, simplifies scaling within a business or project, and enables high availability and fast data recovery.
For all of MongoDB’s benefits, MySQL also has some advantages over MongoDB, such as reliability and data consistency. In addition, MySQL is one of the most secure DBMSS when security is a priority.
Also, when an application needs to treat multiple operations as one transaction, such as an accounting or banking system, a relational database is the best choice. In addition to security, MySQL has a high transaction rate. In fact, MongoDB supports fast insertion of data, while MySQL, by contrast, supports transaction operations and focuses on transaction security.
In general, MySQL is recommended if the project’s data schema is fixed and does not require frequent changes, so the project is easy to maintain and ensures data integrity and reliability.
On the other hand, if the data in the project continues to grow and the data schema is not fixed, MongoDB is the best choice. Because it is a non-relational database, the data can be used freely without the need to define a uniform data structure, so it is easy to update and query the data. MongoDB is typically used for projects that require content management, Internet of Things related services, and real-time analytics.
conclusion
MySQL is an open source relational database in which data is stored in tables, and certain attributes of the data can be related to other tables. MongoDB is also open source, but it is a document database. Therefore, it has no concept of record, its data module is not fixed, so it is a dynamic and flexible database, can insert large amounts of data.
Specific business needs and project priorities should be clearly identified before selecting the best database, and as mentioned earlier, MongoDB outperforms MySQL in handling large volumes of data. This is also true for cloud computing services and projects with frequently changing requirements.
In contrast, data structures and schemas in MySQL are fixed, thus ensuring data consistency and reliability. Another benefit of using MySQL is that data security is higher due to its support for ACID-based transactions. So for projects that focus on these factors, MySQL is the perfect fit.
In short, both databases provide satisfactory performance as long as the usage scenario matches the requirements of the application and the characteristics of the system.
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