Comparing MariaDB vs. Post­gr­eSQL. Which is right for you?

MariaDB and Post­gr­eSQL are two widely used open-source re­la­tion­al database systems. MariaDB is known for its modular storage engines, seamless MySQL com­pat­ib­il­ity and high stability. Post­gr­eSQL has gained a repu­ta­tion for its extensive SQL functions, advanced ana­lyt­ic­al features and ad­apt­ab­il­ity through ex­ten­sions.

What are MariaDB and Post­gr­eSQL?

MariaDB is a re­la­tion­al open-source database system that ori­gin­ated as a fork of MySQL in 2009 and has since evolved sig­ni­fic­antly, with major im­prove­ments in avail­ab­il­ity, com­pat­ib­il­ity and per­form­ance.

Post­gr­eSQL is an object-re­la­tion­al database system that supports advanced data types such as JSON, arrays and GIS fields alongside classic table struc­tures. It is con­sidered highly reliable for complex queries, making it suitable for sci­entif­ic research and complex data analysis. Post­gr­eSQL began de­vel­op­ment at the Uni­ver­sity of Cali­for­nia, Berkeley in 1986 and was released as an open-source project in 1997.

Key features of MariaDB vs. Post­gr­eSQL at a glance

What are the key features of MariaDB?

MariaDB offers numerous features that improve ef­fi­ciency and flex­ib­il­ity. Key high­lights include:

• Wide variety of storage engines: In addition to the standard InnoDB engine, MariaDB provides options such as Aria, TokuDB and Fed­er­atedX. This allows the database to be tailored to specific re­quire­ments.
• Efficient thread pooling: Instead of creating a new thread for every request, MariaDB maintains a pool of worker threads that can process queries quickly and deliver results faster.
• SQL com­pat­ib­il­ity: This par­tic­u­lar database man­age­ment system supports most SQL state­ments as well as more advanced features like JSON operators, window functions and Common Table Ex­pres­sions.
• Virtual columns: Cal­cu­la­tions can be performed directly in the database, elim­in­at­ing the need to implement the same logic across clients.
• Parallel query execution: Since version 10.0, MariaDB has supported executing multiple queries in parallel without per­form­ance loss.

What are the key features of Post­gr­eSQL?

Post­gr­eSQL also has a wide range of powerful features, including:

• JSON support: Post­gr­eSQL can handle schema-less or evolving data models inside re­la­tion­al tables, enabling NoSQL workloads.
• Com­pre­hens­ive feature set: These include Multi Version Con­cur­rency Control (MVCC), point-in-time recovery, granular access controls and online backups. Ex­ten­sions provide ad­di­tion­al cap­ab­il­it­ies such as advanced indexing methods, custom data types and spe­cial­ised operators.
• Real-time data updates: Post­gr­eSQL can process updates in real-time using data fed­er­a­tion and rep­lic­a­tion, reducing the need for tra­di­tion­al ELT/ETL processes.
• Quality-assured de­vel­op­ment: New updates are only included in the release cycle after passing extensive re­gres­sion testing to ensure a stable release cycle.

What are some sim­il­ar­it­ies when comparing MariaDB vs. Post­gr­eSQL?

MariaDB and Post­gr­eSQL share several important char­ac­ter­ist­ics because they are both re­la­tion­al databases:

• Data model: Both follow a re­la­tion­al model, storing data in tables with rows and columns. MariaDB and Post­gr­eSQL both support primary and foreign keys, along with a variety of data types and formats, robust data modelling and indexing for query per­form­ance.
• Open-source licence: Both are open-source projects, allowing de­velopers to view, use and dis­trib­ute the code freely. Both also have active com­munit­ies that con­trib­ute to their ongoing de­vel­op­ment.
• Ex­tens­ib­il­ity: Both systems can be extended. Users can create custom (or user-designed) functions (UDFs) for specific op­er­a­tions or add ex­ten­sions for tasks such as geo­spa­tial pro­cessing.

What are the key dif­fer­ences when comparing MariaDB vs Post­gr­eSQL?

Although MariaDB and Post­gr­eSQL are both open-source re­la­tion­al databases, they differ in several key areas:

• Data model and data types: MariaDB stores data in tra­di­tion­al tables but also supports JSON and dynamic columns. Post­gr­eSQL offers more advanced cus­tom­isa­tion options in terms of data types, functions, operators and supported pro­gram­ming languages.
• Per­form­ance: In terms of MariaDB vs Post­gr­eSQL per­form­ance, both provide modern query op­tim­isers for efficient query execution. MariaDB delivers solid per­form­ance in high through­put trans­ac­tion­al workloads, whereas Post­gr­eSQL is par­tic­u­larly effective when it comes to complex queries.
• Scalab­il­ity: MariaDB primarily relies on vertical scaling but also offers options for ho­ri­zont­al scalab­il­ity, such as Galera Cluster or the Spider Engine for ho­ri­zont­al par­ti­tion­ing. Post­gr­eSQL provides more extensive options for ho­ri­zont­al scalab­il­ity, including streaming, logical rep­lic­a­tion and logical sharding through table par­ti­tion­ing.
• Data input: MariaDB is more flexible with data typing and can auto­mat­ic­ally adjust data types to the target. This is par­tic­u­larly useful for varied data inputs. Post­gr­eSQL is stricter in this regard and displays an error if incoming data doesn’t match the data type.
• Rep­lic­a­tion: MariaDB uses asyn­chron­ous rep­lic­a­tion. Post­gr­eSQL supports both syn­chron­ous and asyn­chron­ous rep­lic­a­tion. In syn­chron­ous mode, data changes are im­me­di­ately trans­ferred to secondary databases. This ensures con­sist­ency even in the event of failures, though with slightly higher latency. MariaDB replica databases respond faster but sometimes lag behind the primary database.

What are the main use cases for MariaDB and Post­gr­eSQL?

MariaDB is primarily used in trans­ac­tion­al en­vir­on­ments and ana­lyt­ic­al workloads. It is widely used for e-commerce platforms, booking and financial systems and data warehouse projects. These require fast OLTP op­er­a­tions (OLTP = Online Trans­ac­tion Pro­cessing) combined with ad-hoc analysis of large datasets.

Post­gr­eSQL is ideal for scenarios that demand advanced data modelling or special data types. Typical use cases include CRM and ERP systems, GIS and geo­spa­tial solutions, financial services and content man­age­ment systems. Post­gr­eSQL is also widely used in IoT platforms, sci­entif­ic research and data mining. Thanks to its strong com­pli­ance with SQL standards, support for custom data types and functions, and active open-source community, Post­gr­eSQL is well suited for long-term projects with unique re­quire­ments.