MongoDB and MySQL share some similarities, but they also have some obvious differences that make them more useful for some users than others. Perhaps the most obvious difference is that MongoDB is a NoSQL database while MySQL only responds to commands written in SQL.

Some potential users want to focus on MongoDB vs. MySQL performance and speed. The following article will help interested people understand the differences between the performance and speed that they can expect from these two database options.




Query language

C++, Java, Python, and others

SQL only




Data storage

Documents (JSON)

Tables (rows and columns)










Referential integrity






Relational interface



Full-text search









Integrity model



Data migration



Customer Story
Customer Story
Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data.
MongoDB MongoDB
Amazon Redshift Amazon Redshift
David Schuman
Dave Schuman
CTO and Co-Founder at
They really have provided an interface to this world of data transformation that works. It’s intuitive, it’s easy to deal with [...] and when it gets a little too confusing for us, [Xplenty’s customer support team] will work for an entire day sometimes on just trying to help us solve our problem, and they never give up until it’s solved.

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Table of Contents

  1. Pros and Cons of MongoDB
  2. Pros and Cons of MySQL
  3. MongoDB vs MySQL Performance
  4. MySQL vs MongoDB Speed
  5. Choosing Between MySQL and MongoDB
  6. Optimize Your Data With Xplenty

Pros and Cons of MongoDB

For the most part, users seem to like MongoDB. Reviews on TrustRadius give the document-oriented database 8.3 out of 10 stars.

Some of the things that authenticated MongoDB users say they like about the database include its:

  • Scalability.
  • Readable queries.
  • NoSQL.
  • Change streams and graph queries.
  • A flexible schema for altering data elements.
  • Quick query times.
  • Schema-less data models.
  • Easy installation.

Users also have negative things to say about MongoDB. Some cons reported by authenticated users include:

  • User interface, which has a fairly steep learning curve.
  • Lack of joins, which can make some data retrieval projects difficult.
  • Occasional slowness in the cloud environment.
  • High memory consumption
  • Poorly structured documentation.
  • Lack of built-in analytics.

For more information on Xplenty's native MongoDB connector, visit our Integration page.

Pros and Cons of MySQL

MySQL gets a slightly higher rating (8.6 out of 10 stars) on TrustRadius than MongoDB. Despite the higher rating, authenticated users still mention plenty of pros and cons of choosing MySQL.

Some of the positive features that users mention frequently include MySQL’s:

  • Portability that lets it connect to secondary databases easily.
  • Ability to store relational data.
  • Fast speed.
  • Excellent reliability.
  • Exceptional data security standards.
  • User-friendly interface that helps beginners complete projects.
  • Easy configuration and management.
  • Quick processing.

Of course, even people who enjoy using MySQL find features that they don’t like. Some of their complaints include:

  • Reliance on SQL, which creates a steeper learning curve for users who do not know the language.
  • Lack of support for full-text searches in InnoDB tables.
  • Occasional stability issues.
  • Dependence on add on features.
  • Limitations on fine-tuning and common table expressions.
  • Difficulties with some complex data types.

For more information on Xplenty's native MySQL connector, visit our Integration page.

MongoDB vs MySQL Performance

When it comes to MongoDB vs MySQL performance, you have to take a subjective look at how each database will affect your projects. While you can find some performance features that sound objectively promising, your team members might never use the features that attracted you to a specific database.

MongoDB Performance

Many people claim that MongoDB performs better than MySQL because it gives them multiple ways to create queries. In other words, you don’t need to know SQL to use MongoDB. While some organizations find that the flexibility does add to MongoDB’s performance, other groups will do fine using SQL queries.

MongoDB also gets performance praise for its ability to handle large unstructured data. Depending on the types of data that you collect, you may benefit significantly from this feature.

MongoDB doesn’t force you into vendor lock-in, which gives you opportunities to improve its performance. If a vendor doesn’t give you superb client services, then you can always search for an alternative that will help you make your database more efficient and flexible.

You can also use Xplenty to simplify the MongoDB ETL process. They integrate easily to give you more control over your data.

MySQL Performance

MySQL performs extremely well for teams that want an open-source relational database that can store information in multiple tables. The performance that you get, however, depends on how well you configure the MySQL database. Configurations should differ depending on the intended use. An e-commerce site, for example, might need a different MySQL configuration than a team of research scientists.

No matter how 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.

If you don’t get the performance that you expect from MySQL data warehouses and databases, you can improve performance by integrating them with an excellent ETL tool that makes data storage and manipulation easier than ever.

MySQL vs MongoDB Speed

In the MySQL vs MongoDB speed debate, MongoDB usually comes out as the winner. MongoDB can accept large amounts of unstructured data much faster than MySQL. It’s difficult to measure precisely how much faster MongoDB is than MySQL when handling large projects. The exact speed that you experience can depend on a variety of factors, such as your internet connection’s bandwidth, the distance between your location and the database server, and how well you organize your data.

All things being equal, though, you can expect MongoDB to handle large data projects much more quickly than MySQL.

Does that mean that you should always choose MongoDB vs. MySQL? Not necessarily. If your organization works with relatively small amounts of data, speed becomes a much smaller concern. When your team uses small amounts of data, you should focus on other database features, such as security, reliability, and flexibility.

Customer Story
Customer Story
Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data.
Amazon Redshift Amazon Redshift
David Schuman
Keith Slater
Senior Developer at Creative Anvil
Before we started with Xplenty, we were trying to move data from many different data sources into Redshift. Xplenty has helped us do that quickly and easily. The best feature of the platform is having the ability to manipulate data as needed without the process being overly complex. Also, the support is great - they’re always responsive and willing to help.

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Choosing Between MySQL and MongoDB

Whether you choose MySQL or MongoDB probably depends on how you plan to use your database.

Choosing MySQL

You will likely prefer MySQL for projects that can benefit from a strong relational database management system, which means storing data in a table format. MySQL also makes an excellent option for cases that need data safety and fault tolerance. If you have high-quality data that you have been collecting over a long period, it makes sense to choose MySQL.

Keep in mind that your team members need to know SQL to use MySQL. If they don’t already know the language, you will need to provide training that brings them up to speed.

Choosing MongoDB

MongoDB can become a better option when you want to take advantage of data clusters and search languages other than SQL. Anyone familiar with a modern coding language will have the basic skills to start using MongoDB. MongoDB also excels at scaling quickly, letting multiple teams collaborate, and storing diverse data formats.

Some people will have difficulty understanding the information stored in MongoDB because it doesn’t use data tables that make browsing easy. Over time, though, users can get used to MongoDB’s document-oriented storage system.

Optimize Your Data With Xplenty

When you take a close evaluation of MongoDB and MySQL, it becomes obvious that both have good and bad points. Few companies release objective data that let you compare speed and performance. Even if you consulted those reports, your system, configuration, and needs could give you a different experience. You can, however, improve the speed, performance, and flexibility of both databases by connecting them to Xplenty.

Xplenty’s ETL solution works quickly to extract information from any database. It can then reformat and add value by transforming the data. Finally, you can load the information destination of your choice. If you already have extensive experience using a specific database, Xplenty will iron out some of the kinks to give you a better experience.

Xplenty users also benefit from its no-code and low-code environment. Extracting data from MySQL becomes much easier when you connect the database to Xplenty because you can find information without learning a query language.

Do you want to learn more about how Xplenty can enhance your experiences with MySQL and MongoDB? Schedule a free demo to discover which features apply to the database you prefer.