MariaDB vs MongoDB: Comparing the Differences

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MariaDB is a successor inspired and designed by the MySQL technology, which is a popular SQL relational database for different applications. MongoDB is a general purpose document database, supported by the database-as-a-service platform, MongoDB Atlas. Its rich feature set and flexible data model make it a world-class alternative to legacy SQL concepts.

This article will help you better understand the differences between MariaDB and MongoDB.

Table of Contents

What is MongoDB?
What is MariaDB?
MongoDB vs MariaDB: Comparison Table
FAQ

What is MongoDB?

MongoDB is a document database built for general-purpose usage. It stores data in an optimized JSON format called BSON (Binary JSON). Documents are then stored in logical groups called collections, and many collections together make up a database. The document model supports many different data types, including strings, dates, numbers, arrays, decimals, nested objects, geo data, and binary data.

MongoDB uses replication and data partitioning to distribute data for high availability and scalability purposes, making it a highly consistent and fault tolerant database. MongoDB supports multiple deployment methods, from running it for free on a variety of platforms and servers starting from your local machine, to a fully blown deployment in the cloud of your choice using MongoDB Atlas. Additionally, MongoDB Enterprise Advanced and MongoDB Atlas offer enterprise-grade security features like authentication, authorization, and LDAP support, as well as end-to-end encryption.

MongoDB’s unified Query API and powerful aggregations, in conjunction with the flexibility of the document model, has made it the most popular general-purpose document database on the market.

What is MariaDB?

MariaDB is an open source relational database management system, created by the original developers of the MySQL database. It uses similar concepts of MySQL, basing its storage model on tables with rows and columns. By design, MariaDB normalizes the data and stores relationships in forms of primary to foreign key connections. The language used to work with MariaDB is SQL, via which you can create tables and database objects, query data, and administrate indexes and functions.

MariaDB leverages various storage engines to power different types of capabilities. For example, different storage engines are needed if users wish to shard their data or structure it in a columnar format.

With the use of MariaDB MaxScale components, MariaDB also allows distributing and load balancing of multiple MariaDB servers as a proxy.

MariaDB and MongoDB: comparison table

The following table will compare some key database features between the two databases.

	MariaDB	MongoDB
Data Model	MariaDB stores data in databases and tables. Each table consists of rows and columns similarly to other RDBMSs. Data should be normalized and separated to different logical tables and connected via relationship semantics. MariaDB does allow some features to store JSON and dynamic columns but it's limited and requires complex syntax.	MongoDB stores documents in an optimized BSON format. Documents are grouped in collections and databases and returned as JSON documents with support for a large number of data types including: strings, numbers, geo data, dates, arrays, decimal, nested objects, binary data. MongoDB also provides a purpose-built solution for time series use cases. Read more on data modeling with MongoDB.
Indexing	MariaDB allows indexes on different columns. As in other relational databases, indexes cover only the columns they are created on. If special indexes, such as geo indexes, are required, external extensions need to be added to the database.	MongoDB supports many index types for various use cases. Secondary indexes on any field are available and supported in different types: Compound, Text, Geo, TTL, Partial, Wildcard and Compound Wildcard indexes.
Query Language	MariaDB uses a SQL dialect similar to MySQL as it is inspired by MySQL. The MariaDB documentation actually recommends using the `mysql` command line utility to connect and run administration commands on a MariaDB.	MongoDB has rich query capabilities provided by its Query API. It also supports a wide variety of modern native drivers, as well as a shell. Data in MongoDB can be edited, deleted, inserted, and queried in many shapes and forms. Queries can use complex operators, as well as the aggregation framework for advanced data manipulation and analytics.
Transactions	MariaDB supports ACID transactions. However, there is no snapshot isolation support, and sharded transactions are only supported with specific storage engines.	MongoDB supports fully ACID-compliant transactions including in sharded clusters and with snapshot isolation.
Concurrency	Concurrency controls in MariaDB depend on the storage engine used. However, MariaDB must use its transaction mechanisms to enforce read isolation. The isolation level can be changed based on specific transaction configurations.	MongoDB allows multiple database users to concurrently access the same data by managing a well defined concurrency control. MongoDB uses document-level locking, so writes to a single document occur either in full or not at all, and clients always see consistent data. Together with those mechanisms, MongoDB supports different read and write concerns for distributed clusters and retryable reads and writes.
High Availability and Scalability	MariaDB relies on different engines and components additional to the MariaDB Server to form a more resilient and scalable cluster—for example the MariaDB MaxScale or the MariaDB Spider engine.	MongoDB was built from the ground up to support distribution of data using replication and sharding mechanisms. Replica sets host an identical copy of the data and elect a primary which receives all the writes, while other nodes are secondaries replicating all the data. Sharding allows you to easily scale your collections across multiple replica sets. With geo-zone sharding, you can also easily manage data sovereignty requirements. The ability to define specific shard keys and reshard collections with zero downtime when a shard key is no longer optimal gives your application a huge advantage when managing massively distributed datasets at scale. The shard key advisor commands will help you refine your shard keys.
Security	MariaDB Enterprise provides the following levels of security: Authentication and authorization through usernames and passwords. TLS/SSL, x509 encryption. Encryption at rest Auditing	MongoDB supports enterprise-grade security mechanisms to secure your MongoDB deployments. Most of them are on by default in the MongoDB Atlas cloud offering: Authentication and authorization using built-in SCRAM or certificates. TLS/SSL, x509, Queryable Encryption and Client Side Field Level Encryption. Server Side storage engine encryption and auditing. LDAP and Kerberos integrations. Additionally, MongoDB Cloud offerings have strong security compliance certifications. Read more on our trust center.
Mobile Support	MariaDB does not support mobile features natively. There are some third-party guides and tools to install MariaDB on mobile devices.	Atlas for the Edge streamlines data management between the database and edge devices. Within this solution, you will find two key components for mobile development: Atlas Device SDKs and Atlas Device Sync Atlas Device SDKs, available for most popular languages, frameworks and platforms, offer a lightweight reactive on-device object-store for mobile/edge/IoT devices. Atlas Device Sync offers offline-first syncronization between MongoDB Atlas clusters and the on-device database with automatic conflict resolution and strong eventual consistency. Changesets may arrive any time that connectivity allows.
Cloud Offerings	MariaDB Enterprise server is provided through a service called SkySQL. It is a database-as-a-service implementation available partially on AWS and GCP. Some features are available on GCP only. No free tier is available. The SkySQL service requires a user to predefine the cluster purpose—e.g., transactional or analytical. Both use cases cannot be covered in a single cluster. Dynamic scaling changes are currently available only on the Xpand storage node types (3 to 6 option only).	MongoDB Atlas, the database-as-a-service platform for MongoDB, offers clusters in all three major cloud providers—AWS, Azure, and GCP—starting from a free tier to a fully blown production cross-region and cross-cloud cluster. Services can be dynamically scaled and cloud providers can be changed as needed. Together with Atlas, you get the advantages of using Atlas App Services application services, Charts, and Data Federation for querying your data lake alongside Atlas clusters, as well as Atlas Search for optimized full text search.
Documentation & Trainings	MariaDB offers documentation for the open source and enterprise version. The company also offers some online courses and training.	MongoDB offers detailed documentation with examples and full tutorials, including a full community and developer hub websites. We also have an online university with free courses available at https://learn.mongodb.com.
Native Data Visualization Tooling	MariaDB does not offer any native data visualization tools, but integrates with third-party applications for data visualization and business intelligence.	MongoDB Charts provides a quick, simple, and powerful way to perform data visualization with MongoDB Atlas data. Additionally, MongoDB Compass provides a GUI client for MongoDB. MongoDB also provides a connector to integrate with popular third-party business intelligence tools.

MariaDB
Data Model	MariaDB stores data in databases and tables. Each table consists of rows and columns similarly to other RDBMSs. Data should be normalized and separated to different logical tables and connected via relationship semantics. MariaDB does allow some features to store JSON and dynamic columns but it's limited and requires complex syntax.
Indexing	MariaDB allows indexes on different columns. As in other relational databases, indexes cover only the columns they are created on. If special indexes, such as geo indexes, are required, external extensions need to be added to the database.
Query Language	MariaDB uses a SQL dialect similar to MySQL as it is inspired by MySQL. The MariaDB documentation actually recommends using the `mysql` command line utility to connect and run administration commands on a MariaDB.
Transactions	MariaDB supports ACID transactions. However, there is no snapshot isolation support, and sharded transactions are only supported with specific storage engines.
Concurrency	Concurrency controls in MariaDB depend on the storage engine used. However, MariaDB must use its transaction mechanisms to enforce read isolation. The isolation level can be changed based on specific transaction configurations.
High Availability and Scalability	MariaDB relies on different engines and components additional to the MariaDB Server to form a more resilient and scalable cluster—for example the MariaDB MaxScale or the MariaDB Spider engine.
Security	MariaDB Enterprise provides the following levels of security: Authentication and authorization through usernames and passwords. TLS/SSL, x509 encryption. Encryption at rest Auditing
Mobile Support	MariaDB does not support mobile features natively. There are some third-party guides and tools to install MariaDB on mobile devices.
Cloud Offerings	MariaDB Enterprise server is provided through a service called SkySQL. It is a database-as-a-service implementation available partially on AWS and GCP. Some features are available on GCP only. No free tier is available. The SkySQL service requires a user to predefine the cluster purpose—e.g., transactional or analytical. Both use cases cannot be covered in a single cluster. Dynamic scaling changes are currently available only on the Xpand storage node types (3 to 6 option only).
Documentation & Trainings	MariaDB offers documentation for the open source and enterprise version. The company also offers some online courses and training.
Native Data Visualization Tooling	MariaDB does not offer any native data visualization tools, but integrates with third-party applications for data visualization and business intelligence.

MongoDB
Data Model	MongoDB stores documents in an optimized BSON format. Documents are grouped in collections and databases and returned as JSON documents with support for a large number of data types including: strings, numbers, geo data, dates, arrays, decimal, nested objects, binary data. MongoDB also provides a purpose-built solution for time series use cases. Read more on data modeling with MongoDB.
Indexing	MongoDB supports many index types for various use cases. Secondary indexes on any field are available and supported in different types: Compound, Text, Geo, TTL, Partial, Wildcard and Compound Wildcard indexes.
Query Language	MongoDB has rich query capabilities provided by its Query API. It also supports a wide variety of modern native drivers, as well as a shell. Data in MongoDB can be edited, deleted, inserted, and queried in many shapes and forms. Queries can use complex operators, as well as the aggregation framework for advanced data manipulation and analytics.
Transactions	MongoDB supports fully ACID-compliant transactions including in sharded clusters and with snapshot isolation.
Concurrency	MongoDB allows multiple database users to concurrently access the same data by managing a well defined concurrency control. MongoDB uses document-level locking, so writes to a single document occur either in full or not at all, and clients always see consistent data. Together with those mechanisms, MongoDB supports different read and write concerns for distributed clusters and retryable reads and writes.
High Availability and Scalability	MongoDB was built from the ground up to support distribution of data using replication and sharding mechanisms. Replica sets host an identical copy of the data and elect a primary which receives all the writes, while other nodes are secondaries replicating all the data. Sharding allows you to easily scale your collections across multiple replica sets. With geo-zone sharding, you can also easily manage data sovereignty requirements. The ability to define specific shard keys and reshard collections with zero downtime when a shard key is no longer optimal gives your application a huge advantage when managing massively distributed datasets at scale. The shard key advisor commands will help you refine your shard keys.
Security	MongoDB supports enterprise-grade security mechanisms to secure your MongoDB deployments. Most of them are on by default in the MongoDB Atlas cloud offering: Authentication and authorization using built-in SCRAM or certificates. TLS/SSL, x509, Queryable Encryption and Client Side Field Level Encryption. Server Side storage engine encryption and auditing. LDAP and Kerberos integrations. Additionally, MongoDB Cloud offerings have strong security compliance certifications. Read more on our trust center.
Mobile Support	Atlas for the Edge streamlines data management between the database and edge devices. Within this solution, you will find two key components for mobile development: Atlas Device SDKs and Atlas Device Sync Atlas Device SDKs, available for most popular languages, frameworks and platforms, offer a lightweight reactive on-device object-store for mobile/edge/IoT devices. Atlas Device Sync offers offline-first syncronization between MongoDB Atlas clusters and the on-device database with automatic conflict resolution and strong eventual consistency. Changesets may arrive any time that connectivity allows.
Cloud Offerings	MongoDB Atlas, the database-as-a-service platform for MongoDB, offers clusters in all three major cloud providers—AWS, Azure, and GCP—starting from a free tier to a fully blown production cross-region and cross-cloud cluster. Services can be dynamically scaled and cloud providers can be changed as needed. Together with Atlas, you get the advantages of using Atlas App Services application services, Charts, and Data Federation for querying your data lake alongside Atlas clusters, as well as Atlas Search for optimized full text search.
Documentation & Trainings	MongoDB offers detailed documentation with examples and full tutorials, including a full community and developer hub websites. We also have an online university with free courses available at https://learn.mongodb.com.
Native Data Visualization Tooling	MongoDB Charts provides a quick, simple, and powerful way to perform data visualization with MongoDB Atlas data. Additionally, MongoDB Compass provides a GUI client for MongoDB. MongoDB also provides a connector to integrate with popular third-party business intelligence tools.

In Summary

MariaDB has expanded and added valuable features to the MySQL database. However, it also diverged from it. It is built on top of legacy SQL core concepts with additional support for new NoSQL era musts like JSON storage, replication, and horizontal scaling. However, the limitations of its foundation and available services will prevent it from fully adapting to the big data and cloud driven nature of modern agile development.

MongoDB was built from the ground up to support cloud elasticity and any amount of data, starting from small on-device databases to large multi-petabyte clusters. It runs the same way anywhere you want, including within our fully featured and scalable cloud database offering, MongoDB Atlas.

FAQ

Is MongoDB better than MariaDB?

It depends on the use case. MongoDB covers a wide range of modern application use cases with proven success at scale across the industry. MariaDB is popular among SQL-based relational web applications.

Does MariaDB use SQL or NoSQL?

MariaDB is a SQL database with RDBMS core concepts. It does offer some extent of NoSQL operations.

How popular is MariaDB?

It's hard to quantify popularity, but DB-Engines ranks MongoDB as the 5th overall most popular database, while MariaDB comes in 13th. Additionally, MongoDB is the 4th most popular database from the Stack Overflow’s 2023 Developer Survey, while MariaDB was the 7th.