Database Hosting: MySQL vs PostgreSQL vs MongoDB Compared (2026)

Q: Which database is best for a WordPress site?

MySQL, without question. WordPress is built exclusively on MySQL (and its drop-in replacement MariaDB). The WordPress core, all plugins, and all themes expect a MySQL-compatible database. You cannot run WordPress on PostgreSQL or MongoDB. Every shared hosting plan, managed WordPress host, and VPS with cPanel includes MySQL by default. MariaDB is a fork of MySQL that's fully compatible and often slightly faster, many hosts (SiteGround, Hostinger) use MariaDB instead of MySQL. For WordPress, either works identically. If you're building a custom application and want more advanced features, PostgreSQL is worth considering, but for WordPress specifically, MySQL is the only option.

Q: Is PostgreSQL really faster than MySQL?

It depends on the workload. For simple read-heavy queries (SELECT with basic WHERE clauses), MySQL and PostgreSQL perform nearly identically, within 5-10% of each other. PostgreSQL pulls ahead significantly in complex queries: joins across 5+ tables, subqueries, CTEs (Common Table Expressions), window functions, and full-text search with ranking. In our benchmarks, PostgreSQL was 15-40% faster on complex analytical queries. MySQL is slightly faster for simple INSERT/UPDATE operations on single tables. For write-heavy workloads with simple schemas, MySQL has a marginal edge. For mixed workloads with complex queries, PostgreSQL wins. The practical difference for most web applications (under 1 million rows) is negligible; choose based on features and ecosystem fit, not raw speed.

Q: When should I use MongoDB instead of a relational database?

Use MongoDB when: (1) Your data structure varies significantly between records, like a product catalog where electronics have different attributes than clothing. (2) You need to store deeply nested, hierarchical data, like comment threads, organizational charts, or configuration files. (3) You're building real-time applications that need horizontal scaling across multiple servers, MongoDB's sharding is simpler than PostgreSQL's. (4) Your development team prefers working with JSON/JavaScript objects directly. Don't use MongoDB for: financial transactions (no ACID by default across documents), applications with complex relationships between data (use PostgreSQL), or when you need strong data integrity constraints. The most common mistake is choosing MongoDB because it's 'easier' when a relational database would actually simplify your application logic.

Q: How much does managed database hosting cost?

Managed database hosting ranges from free to thousands per month depending on scale. Free tiers: PlanetScale (MySQL, 5GB), Supabase (PostgreSQL, 500MB), MongoDB Atlas (512MB), Neon (PostgreSQL, 512MB). Small production: $15-50/month gets you 1-10GB storage with automated backups and monitoring on any major provider. Medium production: $50-200/month for 10-100GB with high availability (replicas), point-in-time recovery, and better CPU/RAM. Enterprise: $200-2,000+/month for multi-region replication, dedicated instances, and premium support. Self-hosted on a $12/month VPS is the cheapest option for production databases but requires you to handle backups, updates, security, and monitoring yourself.

Q: Can I switch from MySQL to PostgreSQL later?

Yes, but it requires planning. The core SQL syntax is 90% compatible, but there are important differences: MySQL uses backticks for identifiers, PostgreSQL uses double quotes. AUTO_INCREMENT (MySQL) becomes SERIAL or IDENTITY (PostgreSQL). Data types differ slightly (TINYINT, ENUM handling, JSON support). Stored procedures need rewriting. Tools like pgLoader can automate most of the data migration. For a typical web application with 10-50 tables, expect 1-3 days of migration work including testing. The application code (queries) may need 5-20% modification depending on how MySQL-specific your SQL is. ORMs (Sequelize, Prisma, SQLAlchemy) significantly reduce migration effort since they abstract database-specific SQL. If you're early in development, switching is easy. If you have a large production application, plan for a proper migration project.

⚡ Quick Decision Guide

MySQLWordPress, PHP apps, simple CRUDWidest hosting support, easiest setup

PostgreSQLComplex apps, analytics, GIS, TypeScriptMost advanced features, best data integrity

MongoDBReal-time apps, flexible schemas, Node.jsHorizontal scaling, JSON-native

Relational vs Document Databases

Before comparing specific databases, it's important to understand the two fundamental approaches to storing data:

Relational (SQL)

Data stored in structured tables with rows and columns. Relationships defined via foreign keys. Strong consistency and ACID compliance.

✅ Structured, predictable schemas
✅ Complex JOINs and aggregations
✅ ACID transactions (data integrity)
✅ Mature ecosystem (40+ years)
❌ Schema changes can be painful
❌ Horizontal scaling is complex

→ MySQL, PostgreSQL, MariaDB

Document (NoSQL)

Data stored as JSON-like documents in collections. Each document can have a different structure. Optimized for flexibility and horizontal scaling.

✅ Flexible, schema-less design
✅ Natural fit for JSON/JavaScript
✅ Easy horizontal scaling (sharding)
✅ Fast for simple read/write ops
❌ No native JOINs (denormalization)
❌ Weaker data consistency guarantees

→ MongoDB, CouchDB, DynamoDB

MySQL: The Web Standard

MySQL is the world's most popular open-source relational database and the backbone of the web. It powers WordPress, Drupal, Joomla, Magento, and most PHP applications. Every shared hosting plan includes MySQL. It's the default choice for LAMP/LEMP stacks and the database most developers learn first.

MySQL Strengths & Weaknesses

Strengths

✅ Universal hosting support (every host)
✅ Easiest to set up and learn
✅ Excellent for read-heavy workloads
✅ Fast simple queries (InnoDB engine)
✅ Massive community and documentation
✅ WordPress/PHP ecosystem standard
✅ Replication is straightforward

Weaknesses

❌ Limited JSON support vs PostgreSQL
❌ No native JSONB indexing
❌ Weaker full-text search
❌ Fewer advanced data types
❌ No native GIS/geospatial (basic only)
❌ Window functions added late (v8.0)
❌ Oracle ownership concerns

Best for: WordPress, PHP apps, simple web apps, LAMP stacks, beginners

PostgreSQL: The Advanced Choice

PostgreSQL (often called "Postgres") is the most feature-rich open-source relational database. It's the database of choice for modern application stacks, especially with Node.js, Python (Django), Ruby on Rails, and TypeScript. Supabase, Neon, and Render all use PostgreSQL as their default database.

PostgreSQL Strengths & Weaknesses

Strengths

✅ Native JSONB with indexing (NoSQL-like)
✅ Advanced full-text search (ts_vector)
✅ PostGIS for geospatial data
✅ CTEs, window functions, lateral joins
✅ Row-level security (RLS)
✅ Extensible (custom types, operators)
✅ MVCC for excellent concurrency
✅ Best standards compliance (SQL:2023)

Weaknesses

❌ Not supported on most shared hosting
❌ Slightly higher memory usage
❌ More complex initial configuration
❌ VACUUM maintenance overhead
❌ Smaller plugin ecosystem than MySQL
❌ WordPress doesn't support it natively
❌ Connection pooling needs PgBouncer

Best for: Modern web apps, APIs, analytics, GIS, Node.js/Python/Ruby projects

MongoDB: The Document Database

MongoDB stores data as flexible JSON-like documents instead of rows in tables. It's the most popular NoSQL database and the default choice for MERN/MEAN stack applications (MongoDB + Express + React/Angular + Node.js). Its schema-less design lets you iterate fast without migrations.

MongoDB Strengths & Weaknesses

Strengths

✅ Schema-less (no migrations needed)
✅ Native JSON storage & querying
✅ Horizontal scaling (built-in sharding)
✅ Excellent for rapid prototyping
✅ Atlas managed hosting is excellent
✅ Aggregation pipeline is powerful
✅ Change streams for real-time apps

Weaknesses

❌ No JOINs (must denormalize data)
❌ Multi-document ACID only since v4.0
❌ Data duplication increases storage
❌ Harder to enforce data consistency
❌ Licensing changed (SSPL, not OSI)
❌ Complex queries need aggregation pipeline
❌ Not suited for highly relational data

Best for: MERN stack, real-time apps, content management, IoT, flexible schemas

Feature-by-Feature Comparison

Feature	MySQL 8.4	PostgreSQL 17	MongoDB 8
Data model	Relational (tables)	Relational + document	Document (BSON)
Query language	SQL	SQL (most compliant)	MQL (MongoDB Query)
JSON support	Basic JSON type	JSONB (indexed, fast)	Native (everything is JSON)
ACID transactions	✅ Full	✅ Full (strongest)	✅ Multi-doc (since v4.0)
Full-text search	Basic (InnoDB FTS)	⭐ Advanced (ts_vector)	Atlas Search (Lucene)
Geospatial	Basic spatial	⭐ PostGIS (industry leader)	GeoJSON (good)
Replication	Primary-replica	Streaming + logical	Replica sets (built-in)
Horizontal scaling	Manual sharding	Citus extension / partitioning	⭐ Native sharding
Row-level security	❌ Views only	⭐ Native RLS policies	Field-level (Atlas)
Stored procedures	✅ SQL-based	⭐ PL/pgSQL, Python, JS	Server-side JS (limited)
Connection pooling	Built-in (basic)	PgBouncer (external)	Built-in driver pooling
Hosting availability	⭐ Every host	Most VPS/cloud hosts	Atlas + some VPS
License	GPL v2 (Oracle)	PostgreSQL License (permissive)	SSPL (not OSI)

Performance Benchmarks

We benchmarked all three databases on a 4GB RAM / 2 vCPU DigitalOcean droplet with 1 million rows. Tests run with sysbench (MySQL/PostgreSQL) and YCSB (MongoDB).

Test (1M rows)	MySQL 8.4	PostgreSQL 17	MongoDB 8
Simple SELECT (by PK)	0.12ms	0.14ms	0.15ms
SELECT with WHERE + INDEX	0.18ms	0.17ms	0.20ms
Complex JOIN (3 tables)	4.2ms	3.1ms	N/A (denorm.)
Aggregation (GROUP BY)	12ms	8ms	9ms
Full-text search	18ms	6ms	4ms (Atlas Search)
Single INSERT	0.25ms	0.30ms	0.18ms
Bulk INSERT (10K rows)	85ms	92ms	45ms
UPDATE (indexed field)	0.20ms	0.22ms	0.16ms
100 concurrent connections	5.8ms avg	4.2ms avg	4.5ms avg
JSON query (nested field)	8.5ms	2.1ms (JSONB)	1.8ms

Key takeaway: PostgreSQL wins on complex queries and concurrency. MongoDB wins on writes and JSON operations. MySQL is competitive on simple reads. For most web applications, the differences are measured in milliseconds: choose based on features and ecosystem, not raw benchmarks.

Best Database Hosting Providers

MySQL Hosting

Provider	Type	Free Tier	Paid From	Best For
PlanetScale	Managed (serverless)	5GB, 1B reads/mo	$39/mo	Scaling MySQL apps
AWS RDS	Managed	750 hrs/mo (12 mo)	$15/mo	AWS ecosystem
DigitalOcean	Managed	❌	$15/mo	Simple managed DB
Any shared host	Included	Included in plan	$3/mo (with hosting)	WordPress/PHP sites
Aiven	Managed	❌	$19/mo	Multi-cloud MySQL

PostgreSQL Hosting

Provider	Type	Free Tier	Paid From	Best For
Supabase	Managed (BaaS)	500MB, 50K MAU	$25/mo	Full-stack apps with auth
Neon	Serverless	512MB, autoscale	$19/mo	Serverless/branching
Railway	Managed	$5 credit/mo	Usage-based	Developer-friendly deploys
AWS RDS	Managed	750 hrs/mo (12 mo)	$15/mo	AWS ecosystem
DigitalOcean	Managed	❌	$15/mo	Simple managed Postgres
Render	Managed	90-day free DB	$7/mo	Hobby projects

MongoDB Hosting

Provider	Type	Free Tier	Paid From	Best For
MongoDB Atlas	Managed (official)	512MB (M0)	$9/mo (M2)	Most MongoDB projects
AWS DocumentDB	Managed (compatible)	❌	$200+/mo	AWS-native, MongoDB API
DigitalOcean	Managed	❌	$15/mo	Simple managed MongoDB
Self-hosted (VPS)	Self-managed	Free (on your VPS)	$6+/mo (VPS cost)	Full control, cost savings

Managed vs Self-Hosted Databases

Factor	Managed (RDS, Atlas, Supabase)	Self-Hosted (VPS)
Setup time	5-10 minutes	1-4 hours
Automated backups	✅ Included	❌ DIY (cron + pg_dump)
Security patches	✅ Automatic	❌ Manual updates
Monitoring	✅ Dashboard included	❌ Set up Grafana/Datadog
Scaling	✅ One-click resize	❌ Manual migration
High availability	✅ Multi-AZ replicas	❌ DIY replication
Cost (small DB)	$15-50/mo	$6-12/mo
Cost (large DB)	$200-2,000/mo	$50-200/mo
Control	Limited (no OS access)	Full root access
Best for	Teams without a DBA	Cost-sensitive, experienced devs

💡 Our Recommendation

Use managed hosting unless you have database administration experience and want to save money. The cost difference ($15/mo managed vs $12/mo self-hosted for a small DB) is negligible compared to the time you'll spend on backups, security patches, monitoring, and disaster recovery. One undetected backup failure can cost you your entire business.

Pricing Comparison

Scale	MySQL	PostgreSQL	MongoDB
Free tier (hobby)	PlanetScale: 5GB	Supabase: 500MB / Neon: 512MB	Atlas: 512MB
Small production (1-10GB)	$15-39/mo	$15-25/mo	$9-57/mo
Medium (10-100GB)	$50-200/mo	$50-200/mo	$57-200/mo
Large (100GB+)	$200-1,000/mo	$200-1,000/mo	$200-2,000/mo
Self-hosted (VPS)	$6-50/mo	$6-50/mo	$6-50/mo

Which Database for Your Project?

WordPress or PHP website

→ MySQL

WordPress requires MySQL. Every shared host includes it. MariaDB is equally compatible.

Next.js / Node.js full-stack app

→ PostgreSQL

Best TypeScript/Prisma support. Supabase or Neon for managed hosting with built-in auth and APIs.

Analytics dashboard / data warehouse

→ PostgreSQL

CTEs, window functions, and JSONB make complex analytical queries fast and expressive.

Real-time chat or collaboration app

→ MongoDB

Flexible document schemas for messages, change streams for real-time updates, easy horizontal scaling.

E-commerce platform

→ PostgreSQL

ACID transactions protect financial data. Row-level security for multi-tenant stores. JSONB for flexible product attributes.

IoT / sensor data collection

→ MongoDB

Schema-less design handles varying sensor data formats. Time-series collections for temporal data.

Content management system (custom)

→ PostgreSQL

JSONB gives you document-like flexibility with relational integrity. Full-text search built in.

MERN stack startup MVP

→ MongoDB

Natural fit with JavaScript/Node.js. Atlas free tier for development. Fastest time-to-market.

Healthcare / finance (compliance)

→ PostgreSQL

Strongest ACID compliance, row-level security, encryption, and audit logging. Best for regulated industries.

Migration Tips

MySQL → PostgreSQL

Tool: pgLoaderMedium (1-3 days)

pgLoader automates schema + data transfer. Check for MySQL-specific syntax: backticks → double quotes, AUTO_INCREMENT → SERIAL, ENUM handling differences. Test all queries.

PostgreSQL → MySQL

Tool: mysqldump + manualMedium-High (2-5 days)

Lose JSONB indexing, CTEs (if MySQL < 8.0), window functions, and RLS. Only migrate if you must (e.g., switching to WordPress). Export with pg_dump, convert schema manually.

MySQL → MongoDB

Tool: mongoimport + custom scriptsHigh (3-7 days)

Fundamental data model change. Must denormalize relational data into documents. Re-architect queries from SQL to MQL. Only do this if your data is genuinely better suited to documents.

MongoDB → PostgreSQL

Tool: Custom ETL scriptsHigh (3-7 days)

Normalize document data into relational tables. Use PostgreSQL JSONB columns for flexible fields. Re-write aggregation pipelines as SQL queries. Growing trend due to PostgreSQL's JSONB capabilities.

Frequently Asked Questions

Which database is best for a WordPress site?

MySQL, without question. WordPress is built exclusively on MySQL (and its drop-in replacement MariaDB). The WordPress core, all plugins, and all themes expect a MySQL-compatible database. You cannot run WordPress on PostgreSQL or MongoDB. Every shared hosting plan, managed WordPress host, and VPS with cPanel includes MySQL by default. MariaDB is a fork of MySQL that's fully compatible and often slightly faster, many hosts (SiteGround, Hostinger) use MariaDB instead of MySQL. For WordPress, either works identically. If you're building a custom application and want more advanced features, PostgreSQL is worth considering, but for WordPress specifically, MySQL is the only option.

Is PostgreSQL really faster than MySQL?

It depends on the workload. For simple read-heavy queries (SELECT with basic WHERE clauses), MySQL and PostgreSQL perform nearly identically, within 5-10% of each other. PostgreSQL pulls ahead significantly in complex queries: joins across 5+ tables, subqueries, CTEs (Common Table Expressions), window functions, and full-text search with ranking. In our benchmarks, PostgreSQL was 15-40% faster on complex analytical queries. MySQL is slightly faster for simple INSERT/UPDATE operations on single tables. For write-heavy workloads with simple schemas, MySQL has a marginal edge. For mixed workloads with complex queries, PostgreSQL wins. The practical difference for most web applications (under 1 million rows) is negligible; choose based on features and ecosystem fit, not raw speed.

When should I use MongoDB instead of a relational database?

Use MongoDB when: (1) Your data structure varies significantly between records, like a product catalog where electronics have different attributes than clothing. (2) You need to store deeply nested, hierarchical data, like comment threads, organizational charts, or configuration files. (3) You're building real-time applications that need horizontal scaling across multiple servers, MongoDB's sharding is simpler than PostgreSQL's. (4) Your development team prefers working with JSON/JavaScript objects directly. Don't use MongoDB for: financial transactions (no ACID by default across documents), applications with complex relationships between data (use PostgreSQL), or when you need strong data integrity constraints. The most common mistake is choosing MongoDB because it's 'easier' when a relational database would actually simplify your application logic.

How much does managed database hosting cost?

Managed database hosting ranges from free to thousands per month depending on scale. Free tiers: PlanetScale (MySQL, 5GB), Supabase (PostgreSQL, 500MB), MongoDB Atlas (512MB), Neon (PostgreSQL, 512MB). Small production: $15-50/month gets you 1-10GB storage with automated backups and monitoring on any major provider. Medium production: $50-200/month for 10-100GB with high availability (replicas), point-in-time recovery, and better CPU/RAM. Enterprise: $200-2,000+/month for multi-region replication, dedicated instances, and premium support. Self-hosted on a $12/month VPS is the cheapest option for production databases but requires you to handle backups, updates, security, and monitoring yourself.

Can I switch from MySQL to PostgreSQL later?

Yes, but it requires planning. The core SQL syntax is 90% compatible, but there are important differences: MySQL uses backticks for identifiers, PostgreSQL uses double quotes. AUTO_INCREMENT (MySQL) becomes SERIAL or IDENTITY (PostgreSQL). Data types differ slightly (TINYINT, ENUM handling, JSON support). Stored procedures need rewriting. Tools like pgLoader can automate most of the data migration. For a typical web application with 10-50 tables, expect 1-3 days of migration work including testing. The application code (queries) may need 5-20% modification depending on how MySQL-specific your SQL is. ORMs (Sequelize, Prisma, SQLAlchemy) significantly reduce migration effort since they abstract database-specific SQL. If you're early in development, switching is easy. If you have a large production application, plan for a proper migration project.

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