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
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.
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.
The following table will compare some key database features between the two databases.
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.||Secondary indexes on any field are available and supported in different types: Compound, Text, Geo, Wild Card, TTL, and Partial.|
|Query Language||MariaDB uses a SQL dialect similar to MySQL as it is inspired by MySQL. The MariaDB documentation actually recommends using the |
Data in MongoDB can be edited, deleted, inserted, and queried in many shapes and forms.
|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|
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.
MariaDB Enterprise provides the following levels of security:
Additionally, MongoDB Cloud offerings have strong security compliance certifications. Read more on our trust center.
MariaDB does not support mobile features natively.
There are some third-party guides and tools to install MariaDB on mobile devices.
Realm also offers an offline-first sync service to Atlas clusters across various client platforms.
Realm sync offers automatic conflict resolution and strong eventual consistency.
MongoDB Realm allows data to sync seamlessly between MongoDB Atlas clusters and user or IoT devices.
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.
|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.
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.
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.