14 Apr Multicloud database strategy: tips for picking the right place for every workload

Your database runs somewhere. The question is: does it run in the right place?

Most companies we talk to don’t start with a multicloud strategy. They end up with one. A Microsoft SQL Server here, a PostgreSQL instance on AWS there, maybe an Oracle database still running on-prem because nobody dared to touch it. Before you know it, you’re managing databases across three or four environments, each with its own logic, its own tooling, and its own blind spots.

That’s not necessarily a problem. But it does mean you need to think carefully about what runs where. Cloud first is the default for many organizations today, and often for good reason. But cloud first doesn’t mean cloud only.

Below, we’ve listed the main options for where your databases can live, with practical use cases and trade-offs for each. Not as a definitive framework, but as a starting point for making more deliberate choices.

On-premises

Running databases in your own data center still makes sense in specific situations. It’s not the default anymore, but for certain workloads it’s the most practical choice.

When it makes sense:

• Your workload requires very low latency. Think of databases that drive a machine park or production line, where every millisecond counts.
• There’s a lot of data moving back and forth between the database and on-premise systems (laptops, machines, local applications). In a cloud setup, the egress costs for all that outbound traffic can add up quickly.
• You’re dealing with highly sensitive data that you want to keep entirely under your own control, on your own infrastructure.

What to keep in mind:

You need a data center. And you need to maintain it: power, cooling, hardware refreshes, physical security. That’s a real ongoing investment. Scaling is harder too. Companies often end up buying more capacity than they need to anticipate future growth, which means paying for resources that sit idle.

Private cloud

A private cloud gives you dedicated infrastructure without the burden of running your own data center. The Cronos Private Cloud, for example, runs entirely in Belgium, which matters for compliance and data sovereignty.

When it makes sense:

• You need to meet strict compliance requirements. Your data has to stay in Belgium or the EU, or you’re working toward NIS2 or ISO 27001 certification.
• You want more control over your environment than a managed public cloud service would allow. More fine-tuning, more customization, configurations tailored to your specific workload.
• You’re running legacy applications that haven’t been modernized yet. These often end up expensive on public cloud VMs that aren’t optimized for them.
• You don’t have (or no longer want) your own data center, but you still want the level of control that comes with dedicated infrastructure.
• You want to work directly with the engineers who manage your environment. In a private cloud setup, the people who designed your database architecture are the same people who monitor it and pick up when something breaks. No anonymous support team on the other side of the world.

What to keep in mind:

A private cloud is scalable, but less elastic than the public cloud. You won’t spin up a new environment in two clicks. And you’ll have fewer out-of-the-box modules at your fingertips: things like native AI integrations or built-in analytics platforms that the hyperscalers bundle into their services. If you don’t need those, that’s no issue. But it’s worth being aware of.

Public cloud

For many workloads, the public cloud is the right call. It gives you speed, scalability, and access to a growing ecosystem of managed services.

When it makes sense:

• Your workload doesn’t have heavy compliance restrictions around data location or sovereignty.
• You want to experiment with new technologies (AI, analytics, machine learning) without building everything from scratch. The hyperscalers have made it very easy to plug these into your database environment.
• You need to scale quickly to handle peak loads, like a web shop during Black Friday or a booking platform during holiday season.
• You want less operational overhead. Managed database services like Google Cloud SQL, Amazon RDS, and Azure Managed Instance handle patching, backups, and basic availability.

What to keep in mind:

The flexibility of the public cloud is also its biggest risk. Costs can escalate quickly, through oversized resource configurations, outbound data transfer charges, or simply because the self-service model makes it easy to click your way into an expensive setup without realizing it. Managed cloud databases are also less customizable. If your workload needs specific tuning, you may hit the limits of what’s configurable. And for latency-sensitive applications, the physical distance to the nearest data center can be a factor, especially if your application wasn’t designed with that in mind. However, one should only be aware of all these aspects, a good governance about what to run where and how to provision will avoid surprises later on.

There’s another nuance worth flagging (which should not be an issue either). Managed database services handle a lot, but they typically don’t cover what ends up costing you the most: performance monitoring to keep resource consumption (and your bill) under control, proper monitoring beyond the default dashboards, restore testing, cloning to dev/test environments, and optimization reviews. Having a managed service doesn’t mean you no longer need a DBA. It means the DBA’s role shifts from infrastructure work to making sure you’re actually getting value from the platform.

Multicloud

Some companies run databases across multiple public clouds. Sometimes that’s a deliberate choice, sometimes it just happened. Either way, it’s a reality worth planning for.

When it makes sense:

• You’re choosing best-of-breed services for different use cases. Maybe Microsoft is already deeply embedded in your organization, which makes Azure a natural fit for some workloads. But Google Cloud might be a better choice for AI-related applications, Oracle for analytics, or AWS for something else entirely. A multicloud approach lets you pick the best platform for each job.
• You want disaster recovery across cloud providers. Recent outages at major cloud platforms have shown that even the largest providers aren’t immune to downtime. Running a DR copy on a second cloud (or on a private cloud) gives you a fallback when one provider goes down.
• You want the benefits of the public cloud, with less dependency on a single vendor.

What to keep in mind:

Every cloud platform has its own way of working, its own monitoring tools, its own logic. Managing databases across two or three clouds means dealing with that complexity. You need more expertise to keep everything running well, and you’ll want a single pane of glass for monitoring rather than jumping between different consoles.

That’s where working with a partner helps. Within the Cronos Group, we collaborate with Cloudar for AWS, Arxus for Azure, and GC Innovate for Google Cloud. For Oracle OCI, we handle it directly as an Oracle Cloud Service Provider. And across all of these, Monin provides the database expertise and unified monitoring to tie it together.

Picking the right place

To make this a bit more tangible, here’s a summary of how the options compare:

The goal isn’t to move everything to one place. It’s to make sure every database is where it makes the most sense, managed by people who understand it, and monitored with the right tools.

Not sure where your databases belong?

If you’re running databases across multiple environments and you’re not sure whether your current setup still makes sense, we’re happy to look at it with you. No pitch, just a conversation about what’s working, what’s risky, and what could be better.

Contact Monin for a database environment assessment