Database Hosting: MySQL, PostgreSQL and MariaDB

Relational databases are the backbone of virtually every modern application: from a corporate CMS to a SaaS platform with millions of users, structured data is stored, queried and replicated through SQL engines. Choosing the right engine and hosting it on properly sized infrastructure is not a minor detail: it determines query latency, service availability and the ability to scale as the business grows.

The three most widely used open-source database engines in production environments are MySQL, PostgreSQL and MariaDB. Each one has a distinct architecture, licensing model and set of strengths. In this article we compare all three engines in depth and explain how to choose the right hosting for each.

We will cover the aspects that matter most in production: hardware requirements, high availability strategies, backup methods, performance tuning and the differences between managed and self-managed hosting.

MySQL: The Most Widely Deployed Engine

MySQL is the most popular relational database management system in the world, with over two decades of history and a massive community. It is currently owned by Oracle Corporation, which maintains both the Community edition (GPL) and the commercial Enterprise editions.

The default storage engine is InnoDB, which provides ACID transactions, row-level locking, foreign keys and crash recovery via the redo log. InnoDB stores frequently accessed data in a buffer pool in RAM, and correctly sizing this buffer is the single most critical factor for MySQL performance.

MySQL supports native asynchronous replication (primary-replica), as well as semi-synchronous replication and the Group Replication architecture for multi-primary clusters. It is the preferred choice for web applications (WordPress, Magento, Laravel), LAMP/LEMP stacks and any environment that prioritises operational simplicity and compatibility with the broadest ecosystem of tools and frameworks.

PostgreSQL: Power and Advanced Features

PostgreSQL is the most advanced open-source relational database engine, with a reputation for robustness, SQL standard conformance and a feature set that surpasses any other open-source RDBMS.

PostgreSQL uses MVCC (Multi-Version Concurrency Control) as its concurrency control mechanism, allowing reads never to block writes and vice versa. This makes it ideal for workloads with high concurrent read and write throughput, such as SaaS platforms, analytics systems and geospatial applications with PostGIS.

One of PostgreSQL's greatest strengths is its extension system: PostGIS for geospatial data, pg_partman for automatic partitioning, TimescaleDB for time series, pgvector for vector search and hundreds more. It also supports JSON/JSONB data types natively with GIN indexes, enabling the combination of relational and document queries within a single engine.

MariaDB: The MySQL Fork with Galera Cluster

MariaDB was born in 2009 as a fork of MySQL created by Michael "Monty" Widenius, the original founder of MySQL, in response to Oracle's acquisition. MariaDB maintains compatibility with the MySQL protocol and most of its APIs, allowing existing applications to migrate with minimal changes.

The most significant difference between MariaDB and MySQL is the native integration of Galera Cluster, a synchronous multi-master replication system that allows writes to any node in the cluster with guaranteed consistency. Galera greatly simplifies high availability architectures by eliminating the need for a single primary node and automatically managing node joins and departures.

MariaDB also includes additional storage engines such as Aria (a crash-safe alternative to MyISAM), ColumnStore for massive OLAP workloads and Spider for transparent sharding. Its licence is pure GPL, without the dual-licensing restrictions of Oracle.

Comparison Table: MySQL vs PostgreSQL vs MariaDB

The following table compares the three engines across the aspects that matter most in production environments:

Criterion	MySQL	PostgreSQL	MariaDB
Licence	GPL + Commercial (Oracle)	PostgreSQL Licence (MIT-like)	Pure GPL
JSON Support	Native JSON, limited functions	JSONB with GIN indexes, advanced operators	JSON compatible with MySQL
Replication	Async, semi-sync, Group Replication	Streaming replication, logical replication	Async + Galera Cluster (synchronous)
Clustering	InnoDB Cluster, NDB Cluster	Patroni + etcd, Citus (sharding)	Native Galera Cluster
OLTP Performance	Excellent for simple reads	Superior for complex queries	Similar to MySQL, optimised for writes
Extensions	Limited plugins	PostGIS, TimescaleDB, pgvector, 300+	Aria, ColumnStore, Spider, Connect

Hardware Requirements for Databases

Database performance depends directly on the underlying hardware. Unlike a web server, where CPU is usually the bottleneck, in databases the three critical resources are RAM, storage and CPU, in that order of importance:

memory RAM (buffer pool / shared_buffers): both MySQL/MariaDB and PostgreSQL keep frequently accessed data in memory. In MySQL, the innodb_buffer_pool_size parameter should be set to 70-80% of total RAM. In PostgreSQL, shared_buffers is set to 25% of RAM, delegating the rest to the operating system cache.
speed NVMe storage: random IOPS determine the speed of queries that do not fit in memory. Enterprise NVMe disks offer microsecond latencies compared with the milliseconds of SATA SSDs, a critical difference for OLTP workloads with thousands of transactions per second.
developer_board CPU: complex queries, joins on large tables and JSON processing consume CPU. For production databases, processors with high per-core frequency (3.5 GHz+) and a minimum of 8 cores on a dedicated server are recommended.

Rule of thumb:

If your dataset fits entirely in the buffer pool (RAM), reads are served from memory with microsecond latencies. If it does not fit, every read that misses the cache will generate a disk I/O operation, multiplying latency by 100x or more.

High Availability: Replication and Clustering

In production environments where downtime has a direct cost, a database without replication is an unacceptable risk. Each engine offers different mechanisms to ensure availability:

sync MySQL/MariaDB primary-replica: the primary node writes changes to a binary log that replicas consume asynchronously. It is simple to configure and allows read distribution across replicas, but if the primary fails, a manual or automated failover is required using tools such as ProxySQL or Orchestrator.
hub Galera Cluster (MariaDB/MySQL): synchronous multi-master replication where all writes are confirmed across all nodes before returning OK to the client. It guarantees strong consistency and allows writes to any node. It requires a minimum of 3 nodes and a low-latency network between them.
shield Patroni (PostgreSQL): a PostgreSQL cluster management tool that automates failover through distributed consensus with etcd or ZooKeeper. Patroni monitors replica status, automatically promotes a replica to primary upon failure and redirects traffic without manual intervention.
route ProxySQL: a high-performance SQL proxy that sits between the application and the database nodes. It distributes read queries across replicas, detects failed nodes and redirects traffic automatically. Compatible with MySQL and MariaDB.

Backup Strategies for Databases

A robust disaster recovery plan requires consistent backups that guarantee data integrity. Each engine offers specific tools:

database mysqldump / mariadb-dump: a logical backup that exports the database as SQL statements. It is simple and portable but slow for large databases (>50 GB). Suitable for daily backups of small and medium databases.
bolt XtraBackup (Percona): a hot physical backup tool for MySQL and InnoDB that copies data files without locking the database. It supports incremental and compressed backups. It is the reference tool for large production databases.
inventory_2 pg_dump / pg_basebackup: pg_dump performs logical backups of PostgreSQL, while pg_basebackup copies the complete data directory at the physical level, allowing replicas to be created or point-in-time recovery when combined with WAL archiving.
backup Veeam Backup: for virtualised environments, Veeam can take application-consistent snapshots of VMs running databases, integrating database backup with the backup of the complete infrastructure.

Performance Tuning

A freshly installed database with default configuration rarely delivers optimal performance. The critical parameters that need tuning depend on the engine:

tune MySQL/MariaDB - buffer pool: innodb_buffer_pool_size should be 70-80% of available RAM. Additionally, innodb_log_file_size should be sized to hold at least 1 hour of writes, and innodb_flush_log_at_trx_commit=1 ensures full ACID durability.
tune PostgreSQL - shared_buffers: set to 25% of total RAM. effective_cache_size at 75% of RAM so the query planner correctly estimates operation costs. work_mem controls the memory per sort or join operation.
lan Connection pooling: both MySQL and PostgreSQL have a limit on simultaneous connections. Tools such as PgBouncer (PostgreSQL) or ProxySQL (MySQL/MariaDB) multiplex hundreds of application connections over a reduced number of real connections to the engine, reducing memory and CPU overhead.

Optimisation tip:

Before scaling hardware, review the slow query logs. In most cases, 80% of performance issues are resolved by optimising SQL queries, adding indexes and adjusting the engine's memory parameters.

Managed vs Self-Managed Hosting

A critical decision when hosting databases is the level of management: installing and operating the engine on a VPS or dedicated server (self-managed) versus using a managed service where the provider handles maintenance, updates and monitoring.

Self-managed hosting offers full control over the configuration, engine version, installed extensions and tuning parameters. It is the preferred option for teams with database administration experience who need to customise every aspect of the environment. However, it requires dedicating internal resources to tasks such as security patching, backup management, 24/7 monitoring and capacity planning.

Managed hosting delegates these operational tasks to the provider, allowing the development team to focus on application logic. EasyDataHost offers managed services for databases that include installation, optimised configuration, automatic backups, proactive monitoring, security updates and specialised technical support.

Database Hosting at EasyDataHost

EasyDataHost provides infrastructure optimised for production databases on dedicated servers and cloud IaaS with enterprise NVMe storage, high-capacity ECC RAM and low-latency connectivity in our Madrid data centre.

check_circle Enterprise NVMe disks: storage with microsecond latencies to maximise database IOPS.
check_circle ECC RAM up to 512 GB: large-capacity buffer pools to keep the entire dataset in memory.
check_circle Automatic backups: daily backups with configurable retention and offsite storage for disaster recovery.
check_circle Data in Spain: Tier III+ data centre in Madrid with guaranteed data sovereignty and GDPR compliance.

Conclusion

The choice between MySQL, PostgreSQL and MariaDB depends on the specific needs of your application, your team and your growth strategy. All three engines are solid, mature and capable of handling demanding production workloads when hosted on properly sized infrastructure.

arrow_right MySQL is the most widely deployed option for web applications, with a massive ecosystem and operational simplicity.
arrow_right PostgreSQL excels with its advanced features, extensions and SQL standard conformance.
arrow_right MariaDB combines MySQL compatibility with Galera Cluster for multi-master high availability.
arrow_right Hardware is critical: RAM for the buffer pool, NVMe for IOPS and high-frequency CPUs.
arrow_right EasyDataHost offers database hosting on NVMe servers with managed support in Spain.

If you need advice on choosing the right database engine or sizing your infrastructure, contact our team to design the solution that best fits your project.

MySQL PostgreSQL MariaDB Databases Infrastructure