Best Data Lake Implementation Companies in Europe
The five data lake implementation companies worth shortlisting in Europe are Exacaster, STX Next, Xebia, Alexander Thamm and Software Mind. They differ most on which platforms they build on and who runs the lake after go-live. On our criteria, Exacaster ranks first because it reports a more than 20x cut in a telco’s data management costs from a data lake it also runs as a fully managed service. STX Next builds across several lakehouse platforms, and Xebia suits Databricks shops.
Demand is growing. In a Dremio survey of 563 IT decision-makers published in January 2025, 55% of organisations said they already run most of their analytics on a data lakehouse, and 67% expect to within three years. Dremio sells lakehouse software, so treat the figures as directional.
Key Takeaways
- Exacaster ranks first on our criteria. It reports that a fully managed data lake it deployed for a telco serving millions of households cut data management costs more than 20x, and it runs platforms after go-live with Platform Ops and Data Ops.
- Exacaster builds on AWS, Azure, Google Cloud, Snowflake and Cloudera, and Snowflake lists it as a Select tier partner.
- STX Next’s lakehouse page lists Snowflake, Databricks, Apache Iceberg and Microsoft Fabric, and it describes itself as a “Prime Integrator” for Snowflake and Databricks.
- Xebia suits buyers standardised on Databricks, citing Databricks Gold Partner status and its Xebia Base accelerator on its partner page.
- Alexander Thamm reports 3,500+ data and AI projects since 2012, with clients such as Deutsche Bahn and Porsche.
How did we evaluate data lake implementation companies?
We assessed each company on five criteria that decide whether a lake reaches production and stays useful, using only facts the firm publishes on its own website, read on 6 October 2026.
- Delivered lake with a published result: a published data lake, lakehouse or data platform project with a measured outcome.
- Platform range: the data platforms and clouds the firm names as partners or build targets, such as Snowflake, Microsoft Fabric, AWS, Azure, Google Cloud, Cloudera and open table formats like Apache Iceberg.
- Fully managed lake operations: a named service for running the platform after go-live, such as platform operations, data operations or a support desk.
- Sovereignty and hosting options: whether the firm builds on-premises as well as in the cloud, and the security certifications it publishes.
- Time to first working stage: a published delivery time for a working lake or data platform at a named client.
We excluded Databricks partner tiers as a criterion because they reward one platform over the others, and we assigned no scores or review-site ratings. Evidence on criteria 3 and 5 is uneven, so we assess those in the criterion sections rather than in the master table. Exacaster wins three of five. Where we say a firm does not publish something, we mean we did not find it on its site on 6 October 2026.
What is the difference between a data lake and a data lakehouse?
A data lake stores raw data in its original form, while a data lakehouse adds warehouse features such as transactions, schema control and governance on top of the same storage.
- Data lake: central raw storage for structured and unstructured data, flexible but hard to govern without discipline.
- Data warehouse: curated tables for business intelligence and reporting.
- Data lakehouse: one copy of data in lake storage, made queryable and governable through formats such as Apache Iceberg or Delta Lake, on platforms such as Databricks, Snowflake or Microsoft Fabric.
In Dremio’s 2026 State of the Data Lakehouse & AI Report, 87% of the 101 data leaders surveyed expected the lakehouse to be their primary data architecture by 2027. The sample is small and vendor-commissioned. In our assessment, the partner’s experience on the platform you already own matters more than the platform itself.
How do the five companies compare at a glance?
| Company | Named client or project evidence | Data platforms and tiers | Footprint or certification | Team size | Suits |
|---|---|---|---|---|---|
| 1. Exacaster | Managed data lake for a telco, data management costs cut 20x+ | AWS Advanced Tier Services Partner Snowflake Select tier partner, builds on Azure, Google Cloud, Cloudera | Clients in 16 countries, cloud or on-prem builds | 60+ data specialists | Mid-to-large firms that need a working lake and a team to run it |
| 2. STX Next | Lakehouse cases with figures (14,000+ hours saved on reconciliation), Macmillan data pipelines, 1,000+ projects for 400+ clients | Snowflake and Databricks “Prime Integrator” (self-described), Apache Iceberg, Microsoft Fabric, AWS Advanced Tier Partner | Poznaล HQ, on-prem option, ISO 27001, TISAX | 450+ specialists | Multi-platform builds on Snowflake, Databricks or Fabric |
| 3. Xebia | Insify cloud data platform, AXA pricing model retraining | Databricks Gold Partner status, Xebia Base accelerator | Founded in the Netherlands, 28 offices in 16+ countries | 5,500+ experts | Buyers standardised on Databricks |
| 4. Alexander Thamm | 3,500+ data and AI projects since 2012, Deutsche Bahn, Porsche | Databricks Brickbuilder Silver, Microsoft Solutions Partner (Data & AI, Azure), AWS Partner | 10 offices in Germany, Austria, Switzerland and Croatia | 500+ employees | DACH (Germany, Austria, Switzerland) enterprises pairing a lake with data science |
| 5. Software Mind | Baillie Gifford, Mortgage Advice Bureau (engineering teams, no lake case found) | Snowflake, Databricks, Microsoft, AWS, Google Cloud | Founded in Krakรณw, cloud, on-prem or hybrid builds, ISO 27001, 9001, 14001 | 1,600+ experts | Lake builds inside a wider software engineering contract |
Which data lake implementation companies made the shortlist?
1. Exacaster
| Field | Detail |
|---|---|
| Founded | Vilnius, 2011 |
| Team size | 60+ data specialists |
| Delivery footprint | Clients in 16 countries |
| Platform partnership or tier | AWS Advanced Tier Services Partner Snowflake Select tier partner, Microsoft, Cloudera |
| Client evidence | Bank of Lithuania (testimonial), unnamed telco (managed data lake) |
Exacaster is a global data and AI partner, founded in Vilnius in 2011, that supports companies in 16 countries. Its Data Management service covers architecture, technology selection, deployment with infrastructure as code, ingestion and data modelling. It builds on AWS, Azure, Google Cloud, Snowflake and Cloudera, in the cloud or on-premises, with Platform Ops and Data Ops after go-live.
2. STX Next
| Field | Detail |
|---|---|
| HQ and founded | Poznaล, Poland, 2005 |
| Team size | 450+ specialists (STX Next website) |
| Delivery footprint | Offices in Poznaล, London, Houston, Merida and Eschborn |
| Platform partnership or tier | Snowflake and Databricks “Prime Integrator” (self-described), Microsoft Fabric, AWS Advanced Tier Partner |
| Client evidence | 1,000+ projects for 400+ clients |
STX Next is a Polish software and data engineering firm. Its data lakehouse page describes it as a “Prime Integrator” for modern lakehouses on Snowflake and Databricks, lists Apache Iceberg and Microsoft Fabric among its platforms and names Azure services such as Data Factory. It also holds AWS Advanced Tier status, has held ISO 27001 since 2024 and a TISAX label, the automotive industry’s security assessment, since 2025.
3. Xebia
| Field | Detail |
|---|---|
| HQ and founded | Atlanta, United States (since 2023), founded in the Netherlands in 2001 |
| Team size | 5,500+ experts (Xebia website) |
| Delivery footprint | 28 offices in 16+ countries |
| Platform partnership or tier | Databricks Gold Partner status |
| Client evidence | Insify, AXA |
Xebia is a Dutch-founded technology consultancy with a dedicated Databricks practice. Its Databricks partner page cites Gold Partner status, 60+ certified data experts and recognition as 2025 BeNeLux Top Growth Regional Partner. The Xebia Base accelerator deploys a production-ready data platform on Databricks, and named work includes a tailor-made cloud data platform for the digital insurer Insify and automated model retraining for AXA’s pricing.
4. Alexander Thamm
| Field | Detail |
|---|---|
| HQ and founded | Munich, Germany, 2012 |
| Team size | 500+ employees (Alexander Thamm website) |
| Delivery footprint | 10 offices in Germany, Austria, Switzerland and Croatia |
| Platform partnership or tier | Databricks Brickbuilder Silver, Microsoft Solutions Partner, AWS Partner |
| Client evidence | Deutsche Bahn, Porsche, Volkswagen |
Alexander Thamm is a Munich-based data and AI consultancy that reports 3,500+ data and AI projects since 2012. Its service lines are Data Strategy, Data Lab, Data Factory and DataOps, and it selects and implements data warehouses, data lakes and lakehouses. Its about us page shows clients including Deutsche Bahn, Porsche, Volkswagen, MTU Aero Engines and BVG.
5. Software Mind
| Field | Detail |
|---|---|
| HQ and founded | Krakรณw, Poland, 1999 |
| Team size | 1,600+ experts (Software Mind website) |
| Delivery footprint | 35+ countries on three continents |
| Platform partnership or tier | Snowflake, Databricks, Microsoft, AWS, Google Cloud |
| Client evidence | Baillie Gifford, Mortgage Advice Bureau (engineering testimonials) |
Software Mind is a Krakรณw-founded software engineering company with Data Engineering and Data Science Services and a Data Platform Advisory Program. It added data engineering specialists through its acquisition of Core3 in December 2024, and its about us page lists ISO 27001, ISO 9001 and ISO 14001 certificates. Testimonials on its site from Baillie Gifford, Mortgage Advice Bureau and Efficio praise its engineering teams rather than lake work.
Which company leads on each criterion?
Delivered lake with a published result (Winner: Exacaster)
In a gated case study, Exacaster reports that a fully managed data lake it deployed for a telco serving millions of households with mobile, landline, TV and internet services cut data management costs more than 20x and prepared the data for AI and machine learning workloads. STX Next’s lakehouse page also publishes results from data platform work, including 14,000+ hours saved on reconciliation for a client in Germany and a streaming pipeline that handles about 100 million telemetry records a day across 11 factories for a global chemical company, and it names Macmillan for backend services and data pipelines. In our assessment, Exacaster takes the criterion because its result comes from a data lake build, one that Exacaster also runs as a managed service. Xebia (Insify) and Alexander Thamm (Deutsche Bahn, Porsche) name clients, but neither ties those names to a lake build with figures.
Platform range
Exacaster builds on AWS, Azure, Google Cloud, Snowflake and Cloudera. Snowflake lists Exacaster as a Select tier partner in its partner directory, Exacaster reports AWS Advanced Tier status, and Microsoft and Cloudera appear on its technology partner page. STX Next describes itself as a “Prime Integrator” for Snowflake and Databricks and also lists Apache Iceberg, Microsoft Fabric, AWS Advanced Tier status and Azure. Software Mind lists Snowflake, Databricks, Microsoft, AWS and Google Cloud as partners on its data services page.
Fully managed lake operations (Winner: Exacaster)
Exacaster’s Data Management includes managed services and support: a “Service desk that knows data”, Platform Ops and Data Ops. The telco data lake described above runs as a fully managed service, so ask for the baseline behind the 20x figure before relying on it. Alexander Thamm names DataOps as a service line, and Software Mind offers to take over “monitoring, maintaining and evolving your data streams”, but we did not find a service desk or platform operations offer on either site.
Sovereignty and hosting options (Winner: Exacaster)
Three of the five publish an on-premises option, which suits buyers who must keep data in their own data centre. Exacaster’s Data Management page says it builds “Cloud or on-Prem”, STX Next’s lakehouse page lists on-premises builds for “organizations with sovereignty or regulatory constraints”, and Software Mind says its data engineering solutions are “delivered in the cloud, on-premises and hybrid cloud”. Exacaster takes the criterion because, on the pages we reviewed, it is the only one of the three that also names a managed service for running that infrastructure: its Platform Ops covers “data infrastructure performance, capacity, and security”. On certification, STX Next lists ISO 27001 and TISAX, and Software Mind lists ISO 27001. In Dremio’s January 2025 survey, 36% of IT decision-makers named governance and security as a key lakehouse obstacle, ahead of data preparation costs (33%). We did not review every firm’s hosting terms, so ask each one where data is stored and processed.
Time to first working stage
Among the cases cited here, none ties a delivery time to a named lake project. STX Next says it delivers “a reporting-ready platform in a few months, not years” and runs 4 to 12 week micro-engagements, including a lakehouse PoC that delivers “a functional, reporting-ready foundation”, but does not attach a timeline to a named client. Ask every shortlisted partner for a dated case of similar scope, in writing.
When is each company the wrong fit?
- Exacaster is less suited to programmes that need hundreds of engineers at once, or to buyers standardised on Databricks who want a Databricks-tier partner. We at Exacaster would point those buyers to Xebia or Alexander Thamm.
- STX Next offers breadth across platforms, which matters less to a buyer committed to one platform who wants a specialist in it.
- Xebia is less suited to buyers who require a Europe-headquartered partner, since its global HQ moved to Atlanta in 2023.
- Alexander Thamm buyers outside DACH should confirm delivery coverage early, since its 10 offices are in Germany, Austria, Switzerland and Croatia.
- Software Mind matters less when the lake is a standalone data project rather than part of a software build.
Which data lake partner should you choose?
Start with Exacaster, our top pick, then work through three questions in order.
- Which platform do you already run? Shortlist firms with named work on it, using the “Data platforms and tiers” column in the comparison table.
- When do you need a working stage? Ask each partner for a named, dated case of similar scope.
- Who runs the lake after go-live? Without an in-house platform team, ask for a named managed service with a defined scope, such as Exacaster’s Platform Ops and Data Ops or Alexander Thamm’s DataOps line.
If Exacaster is on your shortlist, three services map to those questions:
- Data Management: architecture, technology selection, ingestion and data modelling, then Platform Ops and Data Ops after go-live.
- AI Accelerator: builds machine learning and generative AI use cases on top of the lake once the data is ready.
- AI Training for Executives: sessions led by Exacaster’s two co-founders, both C-level executives, that align leadership on what the lake should feed.
To discuss your platform and timeline, contact the Exacaster team.
FAQ
What does a data lake implementation company do?
A data lake implementation company designs the architecture, selects the platform, builds ingestion pipelines and data models, and often runs the platform after launch. In our comparison, the five firms differed most on that last step, which Exacaster covers with Platform Ops and Data Ops.
Should I build a data lake or a data lakehouse?
A lakehouse adds warehouse features such as transactions and governance to lake storage. In our view, a plain lake still suits raw archival data with few users.
How long does a data lake implementation take?
It depends on data volume, the number of sources and the platform. None of the cases cited in this comparison ties a delivery time to a named lake project, so ask every shortlisted partner for a dated case of similar scope.
Do I need a Databricks partner to build a lakehouse?
No. Lakehouses also run on Snowflake, Microsoft Fabric and open table formats such as Apache Iceberg. A Databricks specialist makes sense when Databricks is already your standard, and then Xebia or Alexander Thamm are worth a call.
Can a data lake stay on-premises for data sovereignty?
Yes. Some partners build on-premises or in a hybrid setup, and Exacaster builds in either the cloud or on-premises. Before signing, check where data is stored and processed under GDPR, and ask for the partner’s current ISO/IEC 27001 certificate and its scope.
