AI & compute – Data foundation for machine learning

AI data lake: petabytes under German jurisdiction

Training data grows faster than any plan – object storage grows with it, without booking volume in advance.

Why centron

Why object storage is the foundation

Classic storage systems hit limits with AI data volumes – not in capacity, but in structure.

Scales into petabytes

Large data volumes without complex partitioning or capacity bottlenecks – storage grows with the training data, not the other way round.

Storage and compute separated

Compute scales independently of storage. GPU capacity runs only during training while the data stays put – separating the cost curves.

S3 compatible

Standard tools, SDKs and frameworks speak S3. Existing pipelines can be connected without rewriting them.

In Hallstadt by default

Data resides in our own data centre near Bamberg, with no transfer to third countries – a European alternative to US hyperscalers.

From risk analysis to operations

From data lake to lakehouse

The data lake stores raw data, the data warehouse structured analytics – the lakehouse combines both through table formats such as Delta Lake or Apache Iceberg on the same object storage. For the infrastructure little changes: you need S3-compatible storage that supports the metadata operations of these formats and grows with the data. The analytics layer on top is yours to choose.

Made in GermanyCompany · Data centres · Support
View evidence in the Trust Center
  • Store raw – unstructured, no schema up front
  • S3 compatible – standard tools just work
  • Scale separately – storage and compute
  • Governance – data sovereignty under German law
Recommended modules

The right centron products

Clinics and medical institutions typically implement IT security with these modules – combinable and extensible at any time.

S3 Object Storage
From
5,00\u00a0\u20ac / month
The foundation
  • 0,02 \u20ac per GB
  • Outbound traffic free
  • S3-compatible API
Cloud GPU
From
92,59\u00a0\u20ac / month
For training
  • NVIDIA GPUs
  • Scales separately from storage
  • Hourly billing available
Managed Kubernetes
From
29,99\u00a0\u20ac / month
For pipelines
  • Fixed monthly plans
  • Standard control plane free
  • 99.9% SLA
In brief

What does an AI data lake need as its foundation?

An AI data lake needs object storage that ingests unstructured data in raw form and scales into the petabyte range without coupling storage to compute. The core building block is S3 Object Storage from 5,00\u00a0\u20ac per month at 0,02 \u20ac per gigabyte, complemented by Cloud GPU for training and Managed Kubernetes for pipelines. The infrastructure runs in our own German data centres, certified to ISO 27001 based on IT-Grundschutz (BSI certificate BSI-IGZ-0773) and with an unqualified BSI C5:2020 Type 1 attestation. New accounts receive €200 in starting credit.

Modules and prices
ModulePrice
S3 Object Storagefrom 5,00\u00a0\u20ac / month
Cloud GPUfrom 92,59\u00a0\u20ac / month
Managed Kubernetesfrom 29,99\u00a0\u20ac / month
Industries & sectors FAQ

Frequently asked questions

What distinguishes a data lake from a data warehouse?

The data lake stores raw data without fixing its structure in advance – the schema emerges on read. A data warehouse applies structure on write. For AI projects the data lake is usually the starting point, because while collecting you cannot yet decide which features a later model will need.

Do common tools work with centron S3 Object Storage?

Yes. The API is S3 compatible – tools, SDKs and frameworks that speak S3 work with an adjusted endpoint. Table formats such as Delta Lake or Apache Iceberg build on it too. Existing pipelines can be connected without rewriting them.

What does outbound traffic cost?

Nothing. Outbound traffic is free with centron S3 Object Storage – with training data that is read repeatedly, that is a noticeable difference to providers charging egress fees. What is billed is storage: 0,02 \u20ac per stored gigabyte.
Further reading

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