Learn more about these open-source databases including advantages, disadvantages and uses.
MongoDB vs. MySQL: What Are They?
MongoDB is a free and open-source NoSQL database. As the name ‘NoSQL’ suggests, it is a ‘non-relational/non SQL’ or ‘not only SQL’ database. Its approach to storing data is different from traditional relational databases where tables and rows have been replaced with JSON-like documents. The actual format is binary JSON or BSON.
MongoDB uses collections instead of RDBMS tables, where each collection holds tens of JSON-like documents consisting of key-value pairs. It provides greater flexibility in storing data where the shape of the key-value pairs can be different from one document to another within the same collection. The scalability is easily achieved with MongoDB databases because the documents are self describing, and there is no need for costly schema migrations as in relational databases.
MySQL is a widely known relational database management system(RDBMS) that is free, open source and owned by Oracle. It has almost the same set of features and behaviors as other relational database systems: the database is primarily based on the tables and rows, uses primary keys and foreign keys to maintain the relationships between tables and structured query language(SQL) is used to manipulate data.
Whenever a consumer needs to fetch data rows, a SQL query has to be constructed by joining tables, and adding filters and conditions accordingly. Additionally, relational systems store data that adheres to a predefined database schema. It is a must to match the data objects with this schema to be stored in the relational database. It can be seen as a good safety measure but the flexibility is a trade-off. If there is a need to store data with a new format, the schema has to be changed or migrated which is complex and costly as the database size grows.
MongoDB vs. MySQL: What Are Their Histories?
The story of the invention of MySQL starts with the UNIREG that was developed by Michael Widenius back in 1979, and is a UNIX-based database management tool. Michael partnered with Allan Larsson in 1994, and together they started supporting the development of web applications using UNIREG. They faced issues with the lower-level database engine that wasn’t able to support dynamically generated web content.
In 1995, the two were searching for alternatives and came up with the new relational database MySQL. At the same time, Michael, David Axmark and Larsson partnered to form MySQL AB, which owned the trademark and copyright for the MySQL database server and the dev/support for it.
The initial version was 3.11.1, released in 1995. MySQL became an open-source database under the GNU license. MySQL database software was implemented with C++ and C languages. It uses a SQL parser which is written by yacc. MySQL works in almost all the available platforms such as windows, macOS, Linux, Oracle Solaris, etc. Its latest major version is MySQL 8.0.
Kevin Ryan, Eliot Horowitz and Dwight Merriman started building a platform-as-a-service for productive web application development on the internet in early 2007. They started a company called 10gen to continue the development of this web-centric PaaS with open-source components.
While working on the PaaS, they have come across an amazing trend of modern-day web development where relational databases are popular among web developers to develop web applications. Relational databases have a major drawback in that they can't be horizontally scaled. With the evolution of the web, the facilitation of horizontal scalability of web applications is one of the major prerequisites. They were thinking about building a database that would facilitate horizontal scalability where the database runs across multiple instances with different data stored at each.\ \ It would be very complex to build a relational database that scales horizontally due to several causes. So, the three came up with a NoSQL database called MongoDB that supports horizontal scaling. In 2010, the first version was released, and the latest stable version is MongoDB 6.0 released in 2022.
MongoDB vs. MySQL: What Are the Advantages and Disadvantages?
- High Security. The TLS encryption has been used in MySQL communication, and role-based access control models are in place for authentication which makes MySQL a more reliable database. Because of this solid data security layer, it is used with popular web applications such as Twitter, Facebook, WordPress, etc.
- Low Resource Consumption. MySQL can operate in low memory, CPU environments because it has low memory and CPU consumption compared to other RDBMS.
- Compatibility. MySQL is compatible with most of the platforms like Windows, Linux, MacOs, Solaris, etc.
- Productivity. It supports database-level business logic with triggers and stored procedures which leads to higher productivity.
- Cost. MySQL is free to use and open source where the general public can access the code.
- MySQL is not efficient in handling large databases.
- A predefined database schema has to be modeled beforehand which consumes time and is hard to make post adjustments.
- MySQL is poor at horizontal scaling.
- Lack of documentation.
- MongoDB is a flexible database. It doesn’t expect a fixed schema. Hence, the documents can hold different key-value structures within the same collection which makes it easy to adopt data format changes and saves a lot of time.
- Supports Sharding. Sharding is the technique of splitting big databases into smaller data sets and distributing them among several MongoDB instances. It guarantees that the server's CPU capacity is consumed within limits.
- High-Performance Data Manipulation. Since MongoDB is a document-oriented database, indexing will help with easy access of documents. Generally, it is much faster than the traditional relational databases.
- High Availability. MongoDB uses replication and gridFS techniques to ensure data is available at any given time. On the other hand, these features indirectly increase the overall database performance.
- Easy to Scale. MongoDB can be scaled horizontally which allows the distribution of large amounts of data across multiple machines.
- Easy-to-Store Complex Data Structures. MongoDB stores its data in JSON-like documents. Hence, the arrays and objects can be stored more easily. In addition, hierarchical relationships can be represented conveniently.
- Limited Data Size. The maximum MongoDB document size is 16Mb. It is an unnecessary restriction to storing data in a MongoDB document.
- High Memory Usage. MongoDB doesn’t support joins which leads to data redundancy. In addition, it stores key names for each value pair resulting in excessive memory usage.
- No Stored Procedures and Functions. In relational databases, it is possible to implement stored procedures and functions. Those are not supported in MongoDB. Hence, database-level business logic is not supported.
- No Joins. The table joins are supported in relational systems, but not in MongoDB. In some cases, joins can be implemented by manual coding in MongoDB as well but it will affect the performance.
- Nesting is Limited. MongoDB documents can be nested. Nesting is limited only to 100 levels — which is a drawback when performing complex queries.
SingleStoreDB is a real-time, distributed SQL database that unifies transactions and analytics in a single engine to drive low-latency access to large datasets, simplifying the development of fast, modern enterprise applications. SingleStoreDB provides support for large scale databases with analytics and takes care of most configuration, and also supports various distributions for deployment.
SingleStore is MySQL wire compatible and offers the familiar syntax of SQL, but is based on modern underlying technology that allows infinitely higher speed and scale versus MySQL. This is one of the many reasons SingleStore is the #1, top-rated relational database on TrustRadius.