Switching to Open Source: How Does It Actually Work?

Introduction

Integrating an open source data infrastructure means setting up a new building block — one that connects to your existing systems and evolves with your needs.

You may have read our article on sovereign data platform architecture. Now, the question arises: concretely, what happens when you decide to take the plunge?

This article shows you how an open source data infrastructure integration works, from scratch: what you gain, compatibility with your tools, the concrete steps, and what it requires on your side.

Compatible with Your Tools

The platform adapts to your tools, not the other way around.

Your Visualization Tools

Power BI, Tableau, Metabase, Looker, Excel... It doesn't matter what you're using today. An open source infrastructure exposes standard connectors (SQL, REST API, ODBC/JDBC) that work with all these tools.

Your analysts continue to work as before. They don't even see the difference on the interface side.

Your Business Processes

Your weekly reports, your management dashboards, your automatic exports... Everything continues to work. We integrate new plumbing — your usage doesn't change.

Your Teams

No need to recruit an army of DevOps engineers. Your current teams are trained on the new tools. And honestly, for daily use, there's not much to learn: the interfaces are similar, the concepts identical.

What You Gain

An open source data infrastructure brings three structural advantages over conventional cloud solutions.

Data Ownership

Your data stays with you. On your servers, in your datacenter, or with a trusted European host. You know exactly where it is, and it doesn't move.

Access Control

You, and only you, decide who accesses what. No contractual clause allowing a vendor to access your data "to improve the service". No CLOUD Act authorizing foreign authorities to consult your information.

Predictable Costs

No usage-based billing that can vary greatly from month to month. Costs are predictable: hosting, initial support, and maintenance. The latter can be internalized or entrusted to a service provider — in both cases, it's a controlled budget item.

How It Works

Here are the concrete steps of a typical integration. The duration depends on the complexity of your environment.

Step 1: Understanding Your Situation

We start with a quick audit of your current infrastructure. What data sources? What volumes? What analysis tools? What technical or regulatory constraints?

This assessment allows us to properly size the solution and anticipate attention points.

Step 2: Preparing the Infrastructure

A single server is enough to start. Depending on your volumes and availability needs, we can start with a physical machine, a VM, or a small cluster. We advise you on sizing.

Platform installation takes a few hours. The software components are deployed, configured, secured.

Step 3: Connecting Your Data Sources

This is often the most variable step. Your data can come from anywhere: third-party APIs, CSV files dropped on a server, existing databases, business applications...

We configure the appropriate connectors for each source. Data begins to feed your new platform.

Step 4: Connecting Your Analysis Tools

Your visualization tools are connected to the new infrastructure. We verify that everything works: your existing reports, your dashboards, your usual queries.

On the reporting and analytics side, you have choices. The infrastructure exposes standard connectors that work with all market tools. You can continue with your current solutions, or opt for open source and self-hosted reporting tools — European alternatives exist and integrate perfectly with this type of architecture.

Step 5: Training Your Teams

A short training for your data teams: how to access data, how to create new sources, how to monitor the platform. Nothing revolutionary, just the specifics of your new environment.

All this is done without interrupting your activity. The new infrastructure is set up progressively, while validating that everything works.

A Progressive Build

We don't do "big bang". We start with a first data source, validate that everything works, then expand.

Start Small

No need to connect everything on day one. We start with one or two priority sources — the ones that bring the most value. You get concrete results quickly.

Expand at Your Pace

A new source per week? Per month? We adapt to your operational constraints and your teams' availability. Each added source enriches the platform.

What It Requires on Your Side

For the project to go well, here's what we need from the client side.

The Infrastructure

We take care of it. One of the advantages of open source is that it runs anywhere: existing server, VM, private cloud. We build on what you already have and size the rest.

A Dedicated Contact Person

Someone who knows your current infrastructure and can answer our questions. No need to be available full-time, but responsive when we need information.

What About Migration?

This article covers integration: setting up new infrastructure. But some projects involve replacing an existing system — that's migration, and it's a different undertaking.

Migration is more complex because it requires:

• Analyzing and documenting existing business rules. Before replacing, you need to understand exactly what the current system does — including edge cases nobody documented.
• A migration methodology. Dual-run, mirroring, progressive switchover... The strategy depends on the acceptable level of risk and data criticality.
• Validating scope and volume. Business feasibility (are all rules transferable?) and technical feasibility (can the volumes be handled?).

Datakhi can also support you on this front. The approach is different, the scoping is more thorough, but the skills are the same.

Conclusion

Integrating an open source data infrastructure isn't reserved for large companies with armies of engineers. It's an accessible, progressive project that adapts to your context.

You keep your tools, your processes, your teams. You gain control of your data, predictable costs, and independence from foreign vendors.

At Datakhi, we've been supporting this type of project for several years. Each project is different, but the approach remains the same: understand your situation, propose an adapted solution, and support you until autonomy.

Considering taking back control of your data? Discover our private cloud offering or contact us to discuss.