Modern data stack “Made in Europe”: Where are we?

In initial client meetings or presentations, I often find myself saying: "At The Data Institute, we always think cloud-first when developing technical solutions" and "We're completely at home on all three major hyperscalers!"

While the first statement will likely remain unchanged for the foreseeable future, I see the second one becoming increasingly nuanced amid growing global uncertainty. Beyond the usual questions about security and GDPR compliance with American hyperscalers, more fundamental concerns are emerging: "What happens if an American president suddenly decides to use the sale and operation of American data infrastructure in Europe as political leverage?"

Let me address this directly: I find it difficult to imagine a scenario involving exorbitant price increases or a partial shutdown of US data infrastructure in Europe. The European market—the world's largest cohesive economic region—is simply too important for American software and cloud providers. Additionally, stock market pressure would likely constrain even the most unpredictable presidential actions.

Nevertheless, the current global political and economic landscape provides ample reason to explore alternatives in the data sector and examine the viability of a "Made in Europe" modern data stack.

What Defines a Modern Data Stack?

A Modern Data Stack (MDS) is a collection of best-of-breed tools centered around a data warehouse (or lakehouse) that together form a complete data infrastructure. Unlike monolithic legacy systems, the MDS is characterized by:

• Cloud-native architecture: Scalability and flexibility through cloud technologies
• Decoupled storage and compute: Independent scaling of both resources
• ELT instead of ETL: Data is transformed after loading, not before
• Automation: Reduced manual intervention through orchestration
• Data governance: Integrated measures for data security and quality
• Reduced IT dependency: Only basic IT knowledge required to operate a modern, scalable data infrastructure

US Dominance in the Modern Data Stack

When examining the typical components of a Modern Data Stack, US dominance becomes immediately apparent:

• Cloud infrastructure: Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure
• Data warehousing: Snowflake, Google BigQuery, Amazon Redshift
• Data integration/ELT: Fivetran, Airbyte, dbt
• Orchestration: Airflow, Dagster, Prefect
• Business intelligence: Google Looker, Tableau, Microsoft Power BI
• Data governance: Alation, Atlan
• Version control: GitHub, GitLab, Bitbucket

This market concentration creates the risks mentioned earlier: during geopolitical tensions, regulatory changes, or under an unpredictable US administration, European companies could suddenly find themselves cut off from critical infrastructure.

European Alternatives

Many European stakeholders are increasingly aware of this dependency. Discussions about alternatives have gained significant momentum, particularly with emerging AI technologies and evolving political landscapes. The European Commission's recent AI initiative to establish "AI factories" in Europe exemplifies this growing awareness.

European Cloud Providers with MDS Potential

Beyond AI, building a "Made in Europe" modern data stack requires various components. Several European cloud providers offer interesting capabilities for building data ecosystems, albeit with certain disadvantages compared to American hyperscalers:

Stackhero

This French cloud provider offers a user-friendly platform for managed services including databases, messaging, and storage, with strong security and GDPR compliance:

• Managed database services: Support for PostgreSQL, MySQL, MongoDB, and Redis, comparable to AWS RDS but with lower scalability
• Object storage: S3-compatible storage solution with good performance and lower latency for European users

Disadvantages compared to US-centered MDS:

• Significantly smaller product range compared to AWS, GCP, or Azure
• Lower scalability for very large data volumes
• Less extensive documentation and smaller support community

STACKIT

The German subsidiary of the Schwarz Group operates servers exclusively in Germany and Austria, offering some promising approaches under continuous development:

• STACKIT Data Services: PostgreSQL and MongoDB as fully managed services for transactional database requirements
• STACKIT Data Warehouse: A scalable data warehouse service based on open-source technologies, positioned as a Snowflake alternative with a smaller feature set

Disadvantages compared to US-centered MDS:

• Limited functionality compared to established US solutions
• Lack of integration with many common data engineering tools
• Less sophisticated automation and orchestration features
• Lower market penetration, potentially causing compatibility issues with third-party tools

IONOS Cloud

1&1 IONOS SE provides a European cloud solution focusing on GDPR compliance, performance, and intuitive operation:

• Data Center Designer: Flexible infrastructure configuration for data-intensive applications, similar to AWS CloudFormation but with more limited automation capabilities
• Managed Kubernetes: Service for containerized data workloads, comparable to GKE but with fewer integrated data services

Disadvantages compared to US-centered MDS:

• Lack of specialized, integrated data warehouse solutions like Snowflake or BigQuery
• Less sophisticated APIs and developer tools compared to AWS or GCP
• Slower adoption of new data processing technologies
• Weaker ecosystem integration with modern data engineering tools

Deutsche Telekom Open Telekom Cloud

At first glance, it's evident that Deutsche Telekom pursues a monolithic strategy—everything from a single source—rather than aligning with the Modern Data Stack approach. Based on OpenStack, Telekom offers GDPR-compliant cloud infrastructure with data centers in Germany:

• Open Telekom Cloud MapReduce Service (MRS): A Hadoop-based service for big data processing, comparable to Amazon EMR but less seamlessly integrated with modern data pipelines
• Data Lake Insight (DLI): SQL-based query solution for large datasets, similar to Athena but with lower query speed

Disadvantages compared to US-centered MDS:

• More monolithic architecture that aligns poorly with the modular MDS concept
• Higher costs compared to US hyperscalers, particularly for compute resources
• Less agile product development and slower feature releases
• More difficult to integrate into best-of-breed setups due to partially proprietary API interfaces

Additional European Components

Collibra

One of the few established European components for a modern data stack operates in the data governance space. The Belgium-based company offers comprehensive solutions for data governance, cataloging, quality, and protection. Collibra enables organizations to centrally manage, document, and understand their data. The platform features automated data classification, lineage tracking, and workflow management.

Comparison with US counterparts:

• Generally on par with US competitors in terms of functionality and integration
• More complex deployment and longer time-to-value compared to some lighter alternatives, though this reflects its comprehensive approach rather than a disadvantage

Exasol

This German in-memory database offers high performance and scalability as an alternative to Snowflake. Exasol's column-store technology and patented in-memory architecture enable extremely fast analytical queries that outperform Snowflake in certain benchmarks. The solution can operate both on-premises and in the cloud.

Disadvantages compared to US-centered MDS:

• Less extensive ecosystem of tools and integrations than Snowflake
• Higher entry barrier for smaller companies (complexity and costs)
• Lower market share creates challenges in finding experienced developers

Adverity

The Austrian company offers marketing data integration with governance features that compete with Fivetran or Segment. The platform specializes in marketing data integration and provides pre-built dashboards.

Disadvantages compared to US-centered MDS:

• Primarily focused on marketing data sources, less universal than general ELT tools
• Lower update frequency for new API versions of data sources
• Fewer transformation capabilities compared to dbt
• More limited community and fewer publicly available resources

Conclusion: The Path to a Sovereign European Data Stack

Developing a European modern data stack is both a technological and strategic necessity. While US providers currently offer significant advantages in functionality, market maturity, and integration, European alternatives are gaining importance.

The reality is that European solutions in many areas do not yet match the maturity and functionality of their US counterparts. Critically, products like Snowflake, Databricks, and to some extent BigQuery have evolved beyond simple data warehouse solutions into comprehensive data platforms that process not only SQL but also Python and other programming languages. This enables a much broader range of use cases and substantially expands the potential user base.

For companies, a pragmatic approach is recommended:

1. Risk assessment: Identify critical data infrastructures and evaluate geopolitical risks

2. Hybrid architecture: Prioritize European solutions for sensitive or business-critical applications while using the best available tools for other areas regardless of origin

3. Exit strategy: Develop contingency plans for transitioning from US to European providers if geopolitical risks increase

4. Ecosystem support: Consciously choose European providers where possible to strengthen the European tech ecosystem

At TDI, we advise our clients on precisely this topic: How can organizations build a future-proof modern data stack that balances sovereignty with performance? The answer lies in a thoughtful technology mix that optimally combines the strengths of European and international solutions while developing a strategic roadmap for greater data sovereignty.

Thomas Borlik is co-founder of The Data Institute and leads the data strategy consulting practice. With over 10 years of experience designing and implementing data architectures for companies across industries and sizes, he understands both the challenges and opportunities presented by modern data technologies. As an advocate for pragmatic approaches, he advises organizations at the intersection of technological innovation and strategic data sovereignty.

Want to learn more about European alternatives in the Modern Data Stack or future-proof your data strategy? Contact Thomas directly at thomas.borlik@datainstitute.io or schedule your free consulting meeting.

Photo @jakub_k at unsplash