Managed Database vs Self-Hosted Database: Who Runs the Stack

Mon, 03 Aug 2026 06:30:21 +0900

Overview

A managed database hands the operating system, patching, backups, and failover to a cloud provider, while a self-hosted database keeps the entire stack under your team’s direct control. The choice trades operational convenience against flexibility, cost structure, and how much low-level tuning you’re allowed to do.

Comparison Diagram

Comparison Table

Aspect	Managed Database	Self-Hosted Database
Provisioning & setup	Spin up via console or API in minutes; provider installs and configures the engine	Manually install and configure the OS, storage, and database software yourself
Configuration & tuning access	Limited to exposed parameters and flags; some engine internals and OS access are locked	Full root or admin access to every config file, kernel setting, and storage layout
Scaling	Resize compute or add read replicas with a click or API call; provider automates the process	Provision new hardware and reconfigure sharding or replication topology yourself
Backups & recovery	Automated snapshots and point-in-time restore built into the service	You script, schedule, and test your own backup and restore procedures
Patching & upgrades	Provider applies OS and engine security patches on a maintenance schedule	You plan, test, and execute every patch and major version upgrade
High availability & failover	Multi-AZ replication and automatic failover configured with a toggle	You design, build, and test the replication and failover setup yourself
Monitoring & support	Built-in dashboards and alerts, plus vendor support tickets for engine-level issues	You assemble your own monitoring stack; support is internal or community-based
Cost model	Higher per-hour price that bundles operational labor into the bill	Lower raw infrastructure cost but a hidden cost in engineering time

Key Differences

Managed services abstract patching and OS maintenance behind a provider SLA.
Self-hosted setups grant full root access to tune kernel, storage, and engine internals.
Failover and multi-AZ replication are automated in managed offerings but hand-built elsewhere.
Cost shifts from engineering hours to a recurring subscription fee with managed databases.
Self-hosting permits any custom extension or fork that managed platforms often restrict.

When to Use Each

Managed Database

Horizontal Scaling vs Vertical Scaling: Growing Out vs Growing Up

Sun, 02 Aug 2026 23:47:18 +0900

Overview

Horizontal and vertical scaling are the two fundamental strategies for adding capacity to a system: one adds more nodes working in parallel, the other adds more resources to a single existing node. The choice shapes cost, downtime, fault tolerance, and how much your application architecture has to change to support it.

Comparison Diagram

Comparison Table

Aspect	Horizontal Scaling	Vertical Scaling
Mechanism	Add more machines/nodes to the pool	Add more CPU, RAM, or disk to an existing machine
Implementation	Requires a load balancer and clustering to distribute work	Swap hardware or resize the VM/instance in place
Downtime	Typically none; new nodes join the pool live	Usually requires a reboot or maintenance window
Application requirements	App must be stateless or handle distributed state	App can remain unaware, since it still runs on one node
Cost model	Roughly linear cost per added commodity node	Cost rises steeply at high-end hardware tiers
Fault tolerance	Redundant; a node failing doesn’t take the system down	Single point of failure; that node failing is an outage
Capacity ceiling	Practically unbounded, add nodes as needed	Bounded by the largest machine/instance available
Typical use case	Web-scale services, microservices, cloud-native apps	Databases, legacy monoliths, short-term quick fixes

Key Differences

Horizontal scaling adds more nodes in parallel, while vertical scaling adds more resources to one existing node.
Horizontal scaling needs a load balancer and app-level statelessness; vertical scaling needs no architectural change.
Vertical scaling eventually hits a hardware ceiling; horizontal scaling can grow near-limitlessly.
Vertical scaling usually requires downtime to resize, while horizontal scaling can add capacity live.
Horizontal scaling improves fault tolerance through redundancy; vertical scaling keeps a single point of failure.

When to Use Each

Horizontal Scaling

Cloud on IT Comparison

Managed Database vs Self-Hosted Database: Who Runs the Stack

Overview

Comparison Diagram

Comparison Table

Key Differences

When to Use Each

Horizontal Scaling vs Vertical Scaling: Growing Out vs Growing Up

Overview

Comparison Diagram

Comparison Table

Key Differences

When to Use Each