MariaDB vs PostgreSQL: Which One is Best For You

Last updated on March 22nd, 2022 at 10:47 pm

SQL is a type of database that plays a crucial function in the storage and access of data. With the demands for data growing with the speed of light, the capability to manage data in real-time and scale it with it is essential for most organizations around the globe.

Businesses are accountable for deciding on the best SQL Database given their business needs and requirements.

In the above article, we will look at the distinctions between MariaDB and PostgreSQL. And how these differences affect the selection of a database depending on the nature of the application and limitations.

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After reading the above  article it will be easier to decide which databases will best meet your needs..

Parameters and Features to Consider

MariaDB vs PostgreSQL: Speed

Suppose the amount of data processed in the database is large. In that case, PostgreSQL offers faster reads and writes, making it the best choice in situations where speed of access to data and turnaround time are essential significantly.

MariaDB vs PostgreSQ: Data Typing

PostgreSQL is more strict in its typing and, therefore, if data received is not in line with the destination type of data, PostgreSQL will throw an error and not permit the insertion. PostgreSQL is more inclined to strict integrity of data.

While MariaDB can be more flexible. It can auto correct the received data to match the data type used in the destination. It accepts the data; however, it also emits an alert!

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That is why MariaDB is the preferred choice in numerous modern applications where the information input from users may be unpredictable. However, the application has to be innovative and be able to accept minor discrepancies.

MariaDB vs PostgreSQL: Size

MariaDB is much smaller in footprint than Postgre and is ideal for databases with smaller footprints that require responsiveness quickly and run on smaller computers.

MariaDB vs PostgreSQL: Replication Strategies

The majority of modern applications need physically distributed databases that must be in sync with one another to speed up response times and failure over reliability, performance, and more.

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Replication helps keep databases distributed in sync to ensure that, if one fails, the other will take its place and serve the users. In general, there are two replication strategies available to use for Relational Databases.

Master-Slave Replication


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Between the various physical Database Servers, one assumes the task of the master, and all the others become slaves ( followers, to be precise). The master is accountable for database updates, and every change or update is first transmitted to the master.

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If the change has been committed, the master instructs the slaves of a company to make the same changes and ensure that they are in line with the master. Once a change has been committed to a slave, the individual informs the master that they are ready to receive fresh updates.


  • The resolution of conflict is simple.
  • It is assumed that disputes are frequent, so they enforce ACID compliance more stringently.
  • Other tasks that are not urgent, such as analytics, can be read by the slave and leave the master open for updates to transactions.
  • Backups can be quickly taken from the slaves and without affecting master performance.

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  • All write-ups must be made first in the direction of the master, which makes it a somewhat centralized design. Writers may need to be waited for to propagate.
  • When the master cannot connect before when Slaves have synced, it could cause problems with consistency.
  • If the master fails, there is a risk of significant downtime and potential loss of data.

Master-Master Replication


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The participating database servers are a Master and are also part of the update-anywhere-anywhere model. Updates are sent out to the entire set of Masters in turn and are required to implement them as soon as they are received.


  • If one master cannot function, another can replace it immediately, providing the best availability.
  • Additionally, if any server is down, All the other servers are up to date.
  • Masters are physically far away.

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  • It is challenging to implement, but eager replication systems are complicated.
  • Multi-master replication systems generally assume that conflicts are rare; therefore, they’re somewhat sloppy and unsynchronized and sometimes in violation of the strict requirements of ACID compatibility.

Today, MariaDB offers both Master-Master and Master-Slave strategies. Therefore, it is more flexible with these parameters.

PostgreSQL only supports Master-Slave replicating, which means it’s difficult to choose for applications that require an extremely high level of availability and low geographic latency.

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MariaDB vs PostgreSQL Parameters: Advanced Features

PostgreSQL offers a variety of advanced features, like Materialized Views and partial indexes, which improve your Database performance.

Materialized Views

Before running a regular query, Materialized Views permit pre-calculating costly joins and Aggregation operations and then keeping the results in a table within the database.

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It could improve the speed of complex queries executed frequently and require a lot of data to produce the results. It is beneficial when you have a massive database with many tables that need to be joined regularly to form aggregates.

More information regarding Materialized Views can be found here.

Partial Indexes

Another feature that can speed the process of querying huge and complex Databases that can speed up queries on large and complex Databases are Partial Indexes. Partial indexes are created based on the query results, not on every row in the table (unlike the traditional indexes).

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Often, queries are targeted at specific rows in a table following the recency/high activity if the index is created in a partial form for results of questions that result from these frequently visited rows, resulting in quicker query execution.

More information about Partial Indexes can be found here.

MariaDB vs PostgreSQL: Partitioning

MariaDB supports partitioning through Sharding; however, PostgreSQL cannot partition in the table (s). It can improve MariaDB’s performance and its availability.

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You can also store frequently-accessed data from recent times in an additional partition. In contrast, the less frequently used historical data could be stored in a different section, which will result in faster speeds of access.

MariaDB vs PostgreSQL: JSON and NoSQL Support

MariaDB doesn’t support JSON specifically; however, some solutions can be implemented to make JSON work with MariaDB. However, PostgreSQL has inherently good support for JSON and is an excellent choice for NoSQL needs.

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MariaDB vs PostgreSQL: Table Inheritance and Object Orientation

PostgreSQL has table inheritance support and table inheritance as well as Object IDs (OIDs). It means it is better suited to low-level referential integrity as well as to object orientation.

Below is a table that summarizes the features and their effects when trying to pick the right database software according to your specific business needs.







Suits smaller databases

Suits bigger databases 

Data typing

Flexible data types 

Strict data integrity


Versatile and powerful

Only Master-Slave

Materialized Views, Partial Indexes

Not supported

Quicker complex queries, Faster aggregations 


Faster access to partitioned data 

Not supported

NoSQL and JSon

Not fully supported

Suits NoSQL databases 

If you’re searching for speedy writing and advanced features such as partial indexes and materialized, views choose PostgreSQL.

Suppose you’re looking to provide a more minor but speedy database for mobile apps or websites, in which business logic is the governing factor for the data. In that case, MariaDB could be a suitable option.

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By “business logic rules over dataset”, I refer to situations in which there is lots of complicated calculations and business logic within the code. At the same time, the data is smaller and is not as complex—E.g.

Gaming solutions in which the rules and actions in the game can be implemented into the code. The database is relatively simple; however, it requires quick access.

Simplify ETL Using Company No-code Data Pipeline

There are company can uncoded data pipeline that provides a completely managed solution for setting up data integration with your data warehouse from 100 + information sources (including 30plus completely free sources of data), including SQL Databases such as PostgreSQL, MySQL, etc. and NoSQL Databases such as Elasticsearch, MongoDB, etc. 

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It can manage the flow of data in just a few minutes without writing one piece or code. Its fault-tolerant structure ensures all your information is safe and reliable. These offers you an extremely efficient and automated solution for managing data in real-time and always having data ready for analysis.

Let’s take a look at some Important Features can company provide:

  • Fully managed: The platform does not require maintenance or management as these are an automated platform.
  • Data Transform: It gives you an easy interface to improve or modify the information you want to transfer.
  • Live: Some company can provide real time data movement. So, all your information is ready for analysis.
  • Schema management: These company will automatically identify the schema for the data and then map it to that of the target schema.
  • Live Monitoring Advanced monitoring provides the user with a single point of monitor of all processes that happen within pipelines.
  • Live support: The team is 24/7 to provide exceptional support to customers via chat emails and support calls.


In the end, we hope this discussion helps you identify the unique elements of your business needs and aids you in choosing the best database while also making comparisons between MariaDB against PostgreSQL.

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