MongoDB and MySQL are similar in some ways, but they also have some obvious differences. Perhaps the most obvious one is that MongoDB is a NoSQL database, while MySQL only responds to commands written in SQL.
Here are the things to know about MongoDB vs MySQL performance and speed:
- MongoDB is an open-source database that lets you create multiple queries in various ways. MySQL is an open-source SQL database that offers full-text indexes, a high-speed transactional system, and memory caches that prevent data loss.
- MongoDB and MySQL both handle large amounts of structured data, helping you process information such as names, addresses, credit card details, and spreadsheet data.
- You can enhance the performance of both databases with ETL tools that make data manipulation and storage easier.
- MongoDB accepts large amounts of unstructured data faster than MySQL because of its slave replication and master replication capabilities.
In this article, we'll examine MongoDB vs. MySQL in the areas of performance and speed, to help you determine which one is worth your time. Read on to understand the differences, as well as the pros and cons of each database.
Table of Contents
- What is MongoDB?
- What is MySQL?
- Pros and Cons of MongoDB
- Pros and Cons of MySQL
- MongoDB vs MySQL Performance
- MySQL vs MongoDB Speed
- Choosing Between MySQL and MongoDB
Despite being around for years, MongoDB and MySQL remain two of the most popular open-source databases in 2023. While these technologies are similar in many ways, they also have some differences. Perhaps the most obvious one is that MongoDB is a NoSQL database, while MySQL only responds to commands written in the programming language Structured Query Language (SQL).
Potential users may want to examine MongoDB vs MySQL performance and speed. The following article will help you understand the differences, as well as the pros and cons of each database.
What is MongoDB?
Some of MongoDB's features include:
- Open source
- Document model
- Data replication
- Time-series data
- Database triggers
What is MySQL?
MySQL is a relational database management system based on SQL. Oracle developed MySQL to collect and categorize data according to the relational model.
Some of MySQL's features include:
- Open source
- Character sets
- Client/server architecture
- Data dictionary
- Foreign key constraints
Pros and Cons of MongoDB
For the most part, users seem to like MongoDB. Reviewers on TrustRadius give the document-oriented database a high rating of 8.6/10 (as of February 2023).
Some of the things that authentic MongoDB users say they like about the database are:
- Readable queries
- Change streams and graph queries
- A flexible schema for altering data elements
- Data structure
- Lack of downtime
- Easy query language for developers (MongoDB Query Language)
- Easy installation
- How MongoDB stores data
- MongoDB supports a range of indexing methods
Though many reviews about MongoDB are good, some users do report some negatives, such as:
- A steep learning curve
- Lack of joins
- Occasional slowness in the cloud environment
- High memory consumption
- Poorly structured documentation
- Lack of built-in analytics
Pros and Cons of MySQL
The MySQL database also enjoys a high rating on TrustRadius, with the same score as MongoDB — 8.6/10 (February 2023). Users mention plenty of pros and cons.
Some of the positive features that users frequently mention include MySQL’s:
- Excellent functionality
- Exceptional data security standards
- User-friendly interface
- Rapid processing and indexing
- Ability to handle large datasets
- Join operations
- Security features
- Access control features
- MySQL supports various SQL data types
Of course, even people who enjoy using MySQL note the features they don’t like. Some of their complaints include:
- Reliance on SQL
- Dependence on add-on features
- No Java or Python integration or embedding
- Limitations on common table expressions
- Difficulties with some complex data types
MongoDB vs MySQL Performance
When it comes to MongoDB vs MySQL performance, it's important to consider how each database would affect your projects.
MongoDB offers multiple ways to create queries. MongoDB also gets performance praise for its ability to handle large amounts of unstructured data.
MySQL performs well as an open-source relational database with multiple tables. However you plan to use MySQL, the database’s performance gets a boost from full-text indexes, a high-speed transactional system, and memory caches that prevent you from losing crucial information or work.
You can improve MongoDB vs MySQL performance by integrating either database with an ETL tool that can make data storage and manipulation in real-time easier. For example, you can extract RDBMS data, transform it into the correct format for MongoDB, and load it into the database.
MySQL vs MongoDB Speed
In the MySQL vs. MongoDB speed debate, MongoDB usually comes out as the winner. MongoDB can store large amounts of unstructured data much faster than MySQL (and other databases like PostgreSQL) thanks to slave replication and master replication. Depending on the types of data that you collect, you may benefit significantly from this feature. MongoDB says it’s significantly faster than MySQL for inserting and updating a vast number of records, while MySQL is faster at selecting a high number of records.
MongoDB doesn’t force you into a vendor lock-in, which gives you the opportunity to improve its performance. If a vendor doesn’t provide you with superb client services, then you can search for an alternative to help make your database more efficient and flexible.
You can also use Integrate.io to simplify the MongoDB ETL process. The two integrate easily to give you more control over your data, allowing you to move data to and from MongoDB. For example, you can bring Salesforce data to MongoDB and learn more about your e-commerce and customer service processes.
Choosing Between MySQL and MongoDB
Whether you choose MySQL or MongoDB will probably depend on how you plan to use your database.
MySQL works best for projects that benefit from a strong relational database management system or replication, which means storing data in a table format. MySQL is also an excellent option for users who are concerned with data safety and fault tolerance. Additionally, the high availability of MySQL makes it easy for team members to learn the system.
MongoDB lets you take advantage of data clusters and search languages other than SQL. Anyone familiar with a modern coding language will have the basic skills to use MongoDB. It also excels at scaling quickly, letting multiple teams collaborate, and storing diverse data formats.
Although MongoDB has a lot going for it, some people will have difficulty understanding the information stored in it because it doesn’t use data tables that make browsing easy. You should factor in training time for your staff if you do plan to use this platform. Over time, though, users will get used to MongoDB’s document-oriented storage system, and it will become simpler to use.
You can improve the speed, performance, and flexibility of either database by connecting it to Integrate.io, which features cloud computing capabilities and works incredibly well with big data.
How Integrate.io Can Help With MongoDB vs MySQL Performance
Integrate.io’s ETL solution works quickly to extract information from any database, including MySQL and MongoDB. It can then reformat and transform the data and ensure you adhere to data governance legislation in your region or industry.
When you use Integrate.io with the previously mentioned platforms, you'll find that the platform makes it much easier to move data in and out of the databases, optimizing MySQL vs MongoDB performance. It's also simpler to make that same data available to other systems and users, as needed. If you're not satisfied with how your data is being transferred at the moment, it's time to look into a better option, like Integrate.io.
Here’s a use case for ETLing MongoDB data to Amazon Redshift with Integrate.io:
Integrate.io’s native connector extracts data from MongoDB and places it into a staging area
The no-code data pipeline platform then transforms the data into the correct format for Amazon Redshift
Integrate.io loads this newly transformed data into Amazon Redshift, allowing you to run that data through BI tools
Here’s a use case for ETLing MySQL data to Snowflake with Integrate.io:
Integrate.io’s native connector extracts data from MySQL and places it in a staging area
The no-code data platform transforms the MySQL data into the right format for Snowflake
Integrate.io loads that data into Snowflake, allowing you to generate business intelligence for decision-making
Extracting data from MySQL becomes much easier when you connect the database to Integrate.io because you can find the information you need without having to learn a query language.
Integrate.io can also perform ELT, Reverse ETL, CDC, data observability, and data warehouse insights, making it the perfect platform for all your data pipelines.
Integrate.io’s philosophy is to simplify data integration and remove the jargon associated with moving data to and from MongoDB and MySQL. Schedule a demo now to learn more.