PostgreSQL, MySQL, MongoDB Comparison: Which Database for Which Project?

“Which database should I use?” is one of the most frequently asked questions by DevOps and development teams. The answer is “it depends”; But in order to give the correct answer depending on the situation, it is necessary to know the strengths/weaknesses of each database and in which workload it shines.

In this article, we will compare the 5 most common open source databases as of 2026, explain which one should be chosen in which scenario and how VDS Panel manages these databases.

PostgreSQL: “If I were to make a choice in my entire career, it would be Postgres”

PostgreSQL is the most advanced member of the modern relational database world. Features:

• Full ACID compliance: Transaction security is unconditional
• JSONB: NoSQL style document storage and indexing
• Extensions: PostGIS (GIS), TimescaleDB (time-series), pgvector (AI embeddings)
• Complex queries: Window functions, CTE, recursive queries, full-text search
• Strict type system: Data quality culture

Usage scenarios:

• Data integrity critical systems such as finance, e-commerce, CRM, ERP
• Workload focused on reporting and analytics
• Geo-spatial applications (maps, location)
• AI/ML embedding storage (pgvector)

Weaknesses:

• Slightly heavier on read-heavy workload than MySQL
• Process forks per connection; Solved with connection pool (PgBouncer)

MySQL / MariaDB: “King of the PHP world”

MySQL and MariaDB (fork) are the default of PHP ecosystem like WordPress, Magento, Laravel, Symfony. Still common in 2026.

• High read throughput: Especially mature caching of InnoDB
• Simple replication: Simple master-slave setup
• Ecosystem: Plenty of tools, ORMs, admin tools
• phpMyAdmin: Almost all web hosts offer default

Usage scenarios:

• WordPress, Magento, PrestaShop sites
• Read-heavy analytics (bordering on OLTP rather than OLAP)
• PHP backend, legacy applications
• Simple CRUD APIs

Weaknesses:

• JSON support is more limited than Postgres
• Full-text search is insufficient (Elasticsearch is required)
• Complex analytical queries are behind Postgres

MongoDB: “Schema-free flexibility”

MongoDB document database. Stores a JSON-like document in BSON format.

• Schema-free flexibility: Documents with different structures in the same collection
• Horizontal scaling: Data is distributed automatically with sharding
• Aggregation pipeline: Define complex transformations as a flow
• Geo-queries: 2d/2dsphere indexes built-in

Usage scenarios:

• Content management, catalog, event logging
• IoT data collection (each sensor different scheme)
• Rapid prototyping, MVP
• Real-time analytics (with aggregation)

Weaknesses:

• ACID only at single-document level (multi-doc transaction 4.0+ but expensive)
• No join (lookup limited)
• Schemaless = bug magnet; Postgres JSONB is better in teams that bring discipline to the schema

Redis: “Not the database, but the speed layer”

Redis in-memory data store. It is not used as a Primary DB; It is designed for cache, session store, rate limiting, pub/sub.

• Ultra fast: Sub-millisecond latency as it runs on RAM
• Rich data types: String, list, set, sorted set, hash, stream, geospatial
• Pub/Sub: Simple messaging (not as featured as RabbitMQ)
• Persistence: Durability with RDB snapshot + AOF log is optional

Usage scenarios:

• Session store (web login)
• API response cache
• Rate limiting (IP based)
• Leaderboard (sorted set)
• Distributed lock

Comparison table

Performance examples

Typical benchmark on the same server (4 CPUs, 8 GB RAM, NVMe SSD):

Transaction	PostgreSQL	MySQL	MongoDB	Redis
Simple INSERT	15k/sec	20k/sec	25k/sec	150k/sec
Simple SELECT	30k/sec	40k/sec	45k/sec	200k/sec
Complex JOIN/aggregate	3k/sec	1.5k/sec	N/A*	N/A*
JSON query	10k/sec (JSONB)	5k/sec	35k/sec	N/A*

* No relational join

Redis is used for cache, not primary; PostgreSQL/MySQL/MongoDB compete at the primary tier.

Which one should I choose?

New web application, complex data model: PostgreSQL

WordPress or Magento: MySQL (tool integration)

Content, catalog, IoT, event store: MongoDB

Cache layer, session, rate limit: Redis (on top of primary DB)

Time-series (metrics, logs): PostgreSQL + TimescaleDB extension

Full-text search: PostgreSQL + pg_trgm or Elasticsearch

AI/ML embedding: PostgreSQL + pgvector

Whichever DB you choose with VDS Panel

Database selection is one click when opening a new project in the Panel:

• Installation time ~4 seconds
• User, password, permissions automatically
• Inject connection string into env
• Daily backup active
• PgBouncer (Postgres) or connection pool (MySQL) automatically

It is possible to use multiple DBs: PostgreSQL + Redis within the same project is a common combination. The panel manages them all under the same isolation.

Conclusion

Database selection should follow your project’s business model. Analyze your real workload without getting caught up in technology fads. PostgreSQL is the right answer for most modern web applications, and Redis is the right answer for most caching needs. Choose MongoDB if the document model really gives you an advantage, and choose MySQL/MariaDB if the ecosystem requires it.

VDS Panel manages all five databases in an isolated, redundant and monitored manner per project. For details, you can check the automatic database module or contact form.