Microsoft Fabric and Azure data platforms in Rostock: architecture, capacity and cost

The question we are asked most often by Rostock organisations is whether they need Microsoft Fabric. The answer is frequently no, and saying so has cost us work we did not want.

This page is about building a data platform for an organisation in Rostock, Microsoft Fabric, Azure Synapse, Data Factory and the lakehouse patterns underneath them, with the local economy taken seriously. Rostock's base in ports, terminals and maritime, renewables, and industrial machinery and engineering determines the data volumes, the latency requirements and the retention obligations, and those three things decide the architecture. The client population here is shaped by Baltic port and ferry operations and offshore wind servicing and marine engineering.

Does a Rostock organisation actually need Fabric?

No single condition justifies a capacity. Several together do: data that no longer fits an import model, a requirement for both SQL and notebook access, multiple teams needing governed self-service, retention obligations beyond what a desktop file can hold, or a Premium capacity you already pay for. One analyst maintaining three import models that refresh in twenty minutes does not need a capacity, and buying one will not improve anything.

What the data actually looks like in Rostock

Ports, terminals and maritime

Vessel, container and yard movement data at very high event volume, with berth planning and customs status driving operational decisions hour by hour. Source systems typically include terminal operating system, vessel traffic systems, customs and single-window platforms, crane and equipment telemetry and ERP.

For a platform design, the consequence is specific. Equipment telemetry and the terminal operating system disagree on what counts as a move, so productivity figures vary by source. So the architecture has to make the raw grain replayable rather than aggregating at ingestion, and the first serving model should be a movement and dwell model joining terminal operations to customs status, which exposes whether delays are operational or regulatory.

Tourism, hospitality and events

Booking, channel and rate data with heavy seasonality, plus on-site spend and occupancy that only reconcile once channel commission is accounted for. Gross booking value from online travel agents is compared with direct booking revenue, making the most expensive channel look like the best one.

Systems to plan for: property management system, booking channels and OTAs, revenue management system, EPOS and CRM. Guest data is personal data with cross-border transfer implications when group systems sit outside the region.

Industrial machinery and engineering

Project and configuration data as much as production data: engineered-to-order items, long lead times, and service revenue that outlives the original sale. Project margin is only known at completion, so loss-making contracts are discovered when it is far too late to act. Export control and dual-use classification data should be modelled explicitly where machinery is shipped outside the EU and UK.

A medallion layout for a ports, terminals and maritime business

The medallion pattern is not complicated, and it is routinely implemented badly: a bronze layer that has already lost fidelity, a silver layer with no testable rules, and a gold layer that is really just the silver layer with different names. Here is how we would lay it out for a Rostock client in ports, terminals and maritime.

Capacity sizing and what it really costs

Fabric capacity is billed by capacity unit. An F2 is roughly US$0.36 per hour pay-as-you-go, about US$260 a month, with around 40 per cent off for a one-year reservation. An F64, the smallest SKU at which report consumers no longer need an individual Pro licence, is roughly US$8,400 a month pay-as-you-go or around US$5,000 reserved.

The arithmetic that matters: F64 only becomes cheaper than per-user licensing somewhere in the region of 350 to 600 readers, depending on the discount you actually pay and whether you reserve capacity. Below that, Pro or PPU per user is normally the right answer, and buying capacity for prestige is a straightforward waste of money.

We size capacity by measuring rather than estimating: each workload profiled for compute shape, background refresh against interactive query, concurrency and peak hours, then validated on a short-lived trial capacity with your real data. The output is a sizing model that states expected utilisation at launch, at double the readers, and the specific point at which you would need the next SKU. Always price from the current Microsoft rate card for your region and agreement. Any figure in an article older than a quarter should be treated as an order of magnitude, not a quote.

Direct Lake, import or DirectQuery

Direct Lake reads Delta files in OneLake with no import refresh and no DirectQuery round trip, but unsupported constructs trigger fallback and performance then depends on the SQL endpoint. We test it against an import model on your own data and choose on the measured result. In practice Direct Lake tends to win on large, frequently landing tables, which ports, terminals and maritime workloads often are, while import still wins on smaller models with heavy DAX.

Migrating from what you have now

Few Rostock organisations start from nothing. The realistic options are a serving-layer-first adoption, where Fabric takes the gold layer and reporting while existing engineering stays in place, or a domain-by-domain migration with the old platform retained until each domain is validated. Both avoid a big-bang cutover, which is the pattern that produces the rollbacks we get called in to repair. The reference pipeline we build first is usually the system that hurts most, which here is normally terminal operating system.

Residency, latency and the Germany question

Germany West Central in Frankfurt is the usual choice and gives in-country residency with very low latency to the financial sector. Germany North provides a paired region. Residency alone does not satisfy a German works council or data protection officer. They will also ask about processor chains and access by support personnel, so those answers need preparing.

For Rostock specifically, Germany West Central (Frankfurt) is the normal primary with Germany North (Berlin) as the pair. Latency from Rostock to that region is not usually a constraint for analytical workloads; the constraints that bite are feature availability per region and the processor chain your data protection officer will ask about.

• Betriebsrat co-determination is the single most underestimated factor in German analytics projects: any reporting that could be used to assess individual employee performance generally needs a works agreement before launch.
• MaRisk and BAIT expectations mean financial-sector data lineage and documentation standards are explicit, not inferred.
• The Lieferkettensorgfaltspflichtengesetz requires supply-chain due-diligence data that most ERP estates do not hold in reportable form.

Where to go next

If you are weighing a platform decision for a Rostock organisation, a workload assessment will answer it with evidence in two to three weeks, and the written recommendation is yours whatever you decide. Book a technical review.

We work across Germany and deliver into neighbouring markets regularly. Nearby pages worth reading if your group has sites elsewhere: Kiel, Magdeburg, Freiburg im Breisgau, Kassel, Bremerhaven and Flensburg.

Frequently asked questions