MongoDB is an open-source document-oriented NoSQL database. It saves data in documents and allows users to interact with it using the NoSQL query language. MariaDB is an open-source relational database management system that analyses data using ANSI SQL. MariaDB is a free and open-source database that was established by forking MSQL.

This article talks about MongoDB and MariaDB. It compares 10 critical differences in MariaDB vs MongoDB.

What is MongoDB?

MariaDB vs MongoDB: MongoDB logo | Hevo Data

MongoDB is a document-oriented open-source NoSQL database. It stores the data in documents and supports NoSQL query language to interact with data. MongoDB is very popular among organizations due to its features. 

NoSQL database means it does not store the data in rows and columns compared to traditional databases but instead uses documents that collect key-value pairs to store the data. The key-Value pair allows MongoDB to store the data schema-less and scale them vertically when needed without disrupting the data model. It keeps the data in a storage format known as BSON (Binary Style of JSON document). 

Key Features of MongoDB

  • Cost-Effective DBMS: MongoDB is the popular choice for being one of the popular open-source DBMS systems with the excellent support of multiple programming languages. MongoDB is suitable for storing extensive data.
  • No Primary Key: A typical RDBMS system requires a primary key to be present in the data for indexing and many other reasons. However, in the case of MongoDB, it is not necessary. An automated primary key is linked to the document whenever uploaded.  
  • Schema-less: A typical RDBMS requires a schema to be maintained throughout, whereas in the case of MongoDB, it is a NoSQL database, and hence it doesn’t need a pre-defined schema to store its data. The data in MongoDB is stored in the form of documents containing key-value pairs.
  • Ease of Data Access: MongoDB stores the data in the collection of documents, a key-value pair that makes it easy for any programming language to access the data for analysis and transformations. 

What is MariaDB?

MariaDB vs MongoDB: MariaDB logo | Hevo Data

MariaDB is an open-source RDBMS that works on ANSI SQL to analyze data. MariaDB is created by forking the MSQL and is available as free and open-source software. It is available in various languages such as Perl, C++, Python, etc. Users can use MariaDB in all Windows, Mac, and Linux OS systems.

MariaDB has many inbuilt features, storage engines, improved security systems, and more. 

Key Features of MariaDB

  • Enhanced Security Measures: MariaDB has stringent security measures involving database encryption, Password checks, LDAP authentication, user roles, and many more.
  • Efficient Performance: MariaDB enables caching, threading, and encryptions over the data, making it more performant than MySQL. MariaDB’s performance in fetching the result is exceptional.
  • Efficient User Support: MariaDB has excellent user support for mission-critical production systems around the year. There are also various forums for discussion, chat support, and many more.
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MariaDB Vs MongoDB: Key Differences

1. Database Model

MariaDB has a Relational Database model that requires a pre-defined schema for data to ingest. 

The above picture is from a sample table in MariaDB. As you can see, it contains Rows and Columns which hold the data in a particular fashion(schema), and the entire table is locked to that schema.

MongoDB has a non-relational model which provides schema-less storage of the data in the form of key-value pairs.

MariaDB vs MongoDB: key-value pairs | Hevo Data
MariaDB vs MongoDB: key-value pairs

The above image is from a sample document in MongoDB. As you can see, the data is stored in the form of Key-Value pair, compared to MariaDB, which contains data in the form of Row and Columns.

2. Partitioning Methods

MariaDB offers various partitioning methods like sharding and horizontal partitioning.

MongoDB uses only sharding partitioning, allowing MongoDB to arrange the document efficiently.

3. Replication Methods

MariaDB supports the Master-Slave replication method, and there are four different types of Replication in MariaDB : 

  • Standard Replication
    • Infinite read scale-out is provided.
    • By converting a replica to a primary, high availability is achieved.
MariaDB vs MongoDB: standard replication
MariaDB vs MongoDB: standard replication
  • Ring Replication
    • Scales read and write operations.
    • Doesn’t know how to deal with disagreements.
    • Replication is halted if one of the primary servers fails.
MariaDB vs MongoDB: Ring Replication
MariaDB vs MongoDB: Ring Replication
  • Star Replication
    • Read and write scaling is available.
    • Doesn’t seem to be able to deal with disagreements.
    • To prevent data duplication, replication filters must be used.
MariaDB vs MongoDB: Star Replication
MariaDB vs MongoDB: Star Replication
  • MultiSource Replication
    • It is possible to combine data from various sources.
    • On all replicas, various domains ran in parallel.
MariaDB vs MongoDB: Multi Source Replication
MariaDB vs MongoDB: Multi Source Replication

MongoDB supports the Master-Slave replication and Master-Master replication, allowing members from the replication environment to edit the data.

MariaDB vs MongoDB: Master slave replication | Hevo Data
MariaDB vs MongoDB: Master slave replication

A replica set in MongoDB is a group of mongod processes that maintain the same data set throughout. Replication in MongoDB is done via Replica Set. Replica set provides Data Redundancy and High Availability and provides fault tolerance against the loss. 

4. SQL Syntax

MariaDB is based on ANSI SQL, and hence its syntax is traditional SQL syntax to query and analyze the data. For example, to query the data from a sample employee table, the user can run the following command to get the data – 

SELECT * FROM employee;

The above command will result in employee data fetched from the database tables.

MongoDB is a NoSQL database system, and the data is stored in JSON format in MongoDB. It uses NoSQL syntax and APIs to query data from its collection. For example, in MongoDB, to query the data from the employee table, the user needs to run the following command in python to get the data :

cursor = db.employee.find({})

The above command corresponds to the following SQL statement :

SELECT * FROM employee;

5. Referential Integrity

There is no concept of Foreign keys surrogate keys in MongoDB, and hence the tables aren’t linked together. MongoDB does not have any idea of Referential integrity.

MariaDB is an RDBMS system, and the concept of Foreign key exists. Hence, different tables are very well linked together, which helps to grab the data from any table.

6. Programming Language

MongoDB supports all available programming languages, allowing developers to access MongoDB data via its API. The few supported languages are C++, Python, Java, Scala, Go, NodeJs, Perl, PHP, and many more.

On the other hand, MariaDB had support for only a few languages, and hence sometimes, it isn’t easy to interact with every system. The programming language MariaDB supports is Python, Java, and C/C++.

7. Cloud Support

MongoDB has excellent cloud support with leading cloud technologies in the market, viz. AWS, Azure, and GCP. For more information on MongoDB CLoud solutions, visit the official page here.

On the other hand, MariaDB has only compatible with Azure cloud systems. Recently, MariaDB upgrades to MariaDB SkySQL cloud database, which includes expanded support for Amazon Web Services (AWS).

8. MapReduce Framework

MongoDB has good support for Map-Reduce, which provides excellent data processing capability. For the versions >5.0, the MapReduce is deprecated and instead replaced by Aggregated Pipeline in MongoDB. Aggregated Pipeline provides better performance and usability than MapReduce.

MariaDB doesn’t support Map-Reduce processing, and hence the data processing is slower compared. MariaDB is not recommended for BigData instead it can be used efficiently for OLTP transactions data.

9. Data Format

MongoDB has excellent support for unstructured data because of its schema-less database design. MongoDB stores the data in a collection of documents that stores the value in key-value pairs. Hence the entire database design is schema-less, and users can insert as many key-value pairs within a document.

MariaDB is a relational database, and hence it doesn’t support schema-less data. MariaDB has excellent support for structured data. To define a table in MariaDB user needs to provide the complete schema for that table which must contain column names with datatypes and any constraint.

10. Schema Evolution

MongoDB is a NoSQL database that follows schema-less architecture. Hence, the schema evolution, i.e., manipulating schema, is straightforward in MongoDB. You can easily add a column without much effort. 

MariaDB is a relational database system, and hence schema evolution is a little tricky in this case. You cannot add a new column without affecting the current pipeline.

ParameterMaria DBMongo DB
Database ModelRelational Database Model.Non-Relational Model.
Partitioning MethodsOffers Sharding and Horizontal Partitioning.Offers only Sharding Partitioning.
Replication MethodsSupports Master-Slave Replication.Supports Master-Slave and Master-Master Replication.
SQL SyntaxBased on ANSI SQL.Based on NoSQL.
Referential IntegrityThe concept of Foreign Keys exists.No concept of Foreign Keys or Surrogate keys.
Programming LanguageSupports only a few programming languages.Supports all available programming languages.
Cloud SupportCompatible only with Azure Cloud systems.Excellent cloud support with leading cloud technologies.
MapReduce FrameworkDoes not support Map-Reduce Processing.Good support for Map-Reduce.
Data FormatSupports only structured data.Supports unstructured data.
Schema EvolutionSchemaEvolution is tricky.Schema Evolution is straightforward.

MariaDB vs MongoDB: What should You Choose?

Based on the above parameter, you know that simply choosing one database in MariaDB vs MongoDB is not fair, and hence the choice should be based on the usage.

It has been discovered that in MariaDB vs MongoDB, MongoDB can be a good choice when dealing with big data and needs data analytics on unstructured data. MongoDB is an ideal choice for cloud computing, and it offers high data availability, providing instant and automatic data recovery and database replication.

MariaDB is best suited for structured data and performs very well with the Azure cloud system. It works well with software that requires storing data in a relational database. 

Conclusion

Choosing one database over another is a cumbersome task. Hence this article tried to compare MariaDB vs MongoDB based on different parameters to be easy for you to choose based on your use case.

However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your MariaDB or MongoDB Database can seem to be quite challenging. If you are from non-technical background or are new in the game of data warehouse and analytics, Hevo Data can help! Learn more about MongoDB vs SQL Server.

Hevo Data will automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc. This platform allows you to transfer data from 150+ multiple sources to Cloud-based Data Warehouses like Snowflake, Google BigQuery, Amazon Redshift, etc. It will provide you with a hassle-free experience and make your work life much easier.

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FAQ

Is Hadoop better than SQL?

Hadoop and SQL serve different purposes; Hadoop excels in processing large-scale unstructured data, while SQL is better for structured data queries and relational database management.

Is Hadoop SQL or NoSQL?

Hadoop is neither SQL nor NoSQL; it is a framework for distributed data storage and processing, but it supports SQL-like querying through tools like Hive.

What is the difference between Hadoop and MySQL?

Hadoop handles distributed, unstructured data processing using HDFS, while MySQL is a relational database for managing structured data with SQL.

Muskan Kesharwani
Customer Experience Executive, Hevo Data

Muskan Kesharwani has over two years of experience troubleshooting intricate issues and consistently delivering on time-sensitive tasks. She demonstrates high proficiency in navigating Hevo's internal ETL architecture. Her expertise spans various data sources, including Salesforce, HubSpot, and Stripe. Muskan is also skilled in Python, MySQL, and other technical tools, ensuring comprehensive and practical support for Hevo's clients.