European Analytics

No worries. This will not become any kind of polarized post. But if you want to go and pick your analytics and any kind of data software providers not from the US and you really want to go for European options, here is a collection of option but also a good reminder what would be missing.

Obviously, if you've followed all the Google Analytics alternative discussions, where your data is saved definitely has an impact. The data storage is already something today you need to take into account. Now we can add another dimension: the somewhat unsecure future of how our relationship will develop between the US and Europe. I don't know if you can add tariffs on software-as-a-service products, but maybe you can 🤔 😁.

This list is just off the top of my head. So if you know other tools that would fit in here, please let me know. I'm setting up a directory of European data and analytics solutions, so just let me know and I will add it (link at the bottom of the post).

Now,what qualifies as a European analytics and data solution? This makes it already a little bit harder because there will definitely be edge cases. The first decision I made is to include UK-based companies. Yes, the UK left the EU, but for me, they're still part of Europe, and in our hearts they still kind of belong to the EU, even when technically they don't anymore. But if you're optimizing for data storage within the EU, you have to take this into account since if the data center is in London, it's not in the EU anymore.

Let's start the list.

Classic Digital Analytics

When we talk about digital analytics, we often refer to tools like Google Analytics 4. This category encompasses a wide range of analytics solutions, from simple tracking tools to more advanced platforms. However, classic digital analytics solutions are generally not specialized for highly professional use cases—instead, they work well for most websites and applications to gather behavioral data.

Below, I'll walk you through some of the European alternatives in this space.

Piwik PRO (PL)

The most obvious entry in this category is Piwik PRO. It started as a fork of the original Piwik project, which later evolved into Matomo—but I'll get to that shortly.

Unlike Matomo, Piwik PRO is not open source and never was. The company is based in Poland, with additional offices across Europe and beyond. If you choose their European hosting, your data remains within the EU, making it a strong alternative to Google Analytics for businesses concerned with data privacy.

For those with experience in Google Analytics Universal, Piwik PRO feels like a natural fit. It shares many similarities with GA while adding enhanced privacy controls. You get more granular configuration options for a privacy-focused analytics setup, along with a built-in tag manager—similar to Google Tag Manager, but seamlessly integrated within the platform.

A major advantage of Piwik PRO is its consent management feature, which works smoothly with its tag manager and analytics tools. This makes it significantly easier to manage consent settings compared to the often cumbersome setup required with Google Tag Manager.

If you're looking for a no-brainer alternative to Google Analytics 4, Piwik PRO is an excellent choice.

Plausible Analytics (EE)

Plausible Analytics is another strong contender, though it has fewer features than Piwik PRO. It's a great choice for those who only need core metrics to understand their website's performance.

Unlike Piwik PRO, Plausible does not include a tag manager or consent management, so you'll need to handle those separately. However, it offers a unique advantage: you can configure it to avoid tracking individual users altogether.

For example, if metrics like returning users aren't critical to you, Plausible lets you run an analytics setup that collects anonymous, privacy-friendly data.

Developed by two indie developers in Europe, Plausible is a lean and well-designed solution. It's also affordable, making it a great choice if you want a privacy-friendly alternative without unnecessary complexity.

Simple Analytics (NL)

Simple Analytics falls into a similar category as Plausible. It doesn't have the extensive features of Piwik PRO or Google Analytics, but for many use cases, it's 100% sufficient.

Before implementing an analytics solution, it's always worth asking: What features do I actually need? If your requirements are straightforward, Simple Analytics can be a perfect fit.

This tool is developed by an indie creator in the Netherlands, making it another European-based solution. If you value supporting small, independent teams, this is a great product to consider.

Matomo (NZ)

Matomo originated as Piwik before evolving into its current form. Today, it's mostly known through Matomo Cloud, the managed service operated by InnoCraft, a company based in New Zealand.

However, Matomo's founder, Matthieu, started the project in France, and the tool retains strong European roots.

What sets Matomo apart?

It's still open source – You can self-host it on your own servers if needed. It's the go-to choice for privacy-conscious organizations – If you need an analytics tool that minimizes privacy discussions and concerns, Matomo is a safe bet. It can be configured to collect almost no personal data, making it one of the most privacy-friendly solutions available.

There can be a nice adoption of the IBM quote:

"No one gets fired for choosing Matomo when privacy concerns are on the table."

For organizations prioritizing compliance and data protection, Matomo is a solid addition to this list.

Classic digital analytics tools provide behavioral insights for websites and applications, but not all solutions are created equal.

• If you need a GA4 alternative with a built-in tag manager and consent management, go for Piwik PRO.
• If you want simpler analytics with a strong privacy focus, check out Plausible or Simple Analytics.
• If privacy compliance is your biggest concern, Matomo is your best bet.

Ultimately, the best tool depends on your specific needs—so before choosing a solution, ask yourself: How much complexity do I really need?

Product Analytics

While classic digital analytics often includes marketing analytics, product analytics is a different category of tools altogether.

Product analytics requires a specific event schema, which tools like Piwik PRO and Matomo don't provide. It also needs specialized reports that go deep into user behavior, such as funnel analytics, cohort analytics, and advanced segmentation. These are the hallmarks of product analytics, and you typically find them in tools like Amplitude or Mixpanel. But what are the European alternatives to these US-based solutions?

PostHog (~UK)

PostHog is a bit of a tricky case. Technically, it's a US-based company—likely due to funding reasons—but it originally started in the UK. The founding team was based there, and PostHog still has a strong developer presence in Europe. So, while it's not a purely European solution, it at least comes with an asterisk.

PostHog has a strong product analytics offering and has expanded beyond that. It now also includes classic web analytics features and data warehouse integrations, allowing you to bring event data from your warehouse into PostHog for analysis.

PostHog still has an open-source core, so you can check out the software yourself. However, most users rely on PostHog's managed service, which can be hosted on European servers.

If you're looking for the closest alternative to Mixpanel or Amplitude, PostHog is the way to go.

Mitzu (HU)

Mitzu is similar to PostHog in some ways but also quite different.

Mitzu is a Hungarian software company and a relatively young player in the space. I've used it in several projects, and what makes it stand out—especially compared to Amplitude and Mixpanel—is that Mitzu does not have its own SDKs. Instead, Mitzu works directly on your data warehouse.

This means you don't send events directly to Mitzu. Instead, you store event data in your warehouse first and then use Mitzu on top of it—similar to how a BI tool works.

Why is this powerful? Once connected to your event data table, it enables funnel reporting, cohort analysis, segmentation, and more.

Because Mitzu sits on top of your data warehouse, you have much more control over your data. You can prepare, clean, and transform event data before sending it to Mitzu, and you can refactor data easily—something that's a nightmare in traditional product analytics tools.

In SDK-based tools like Amplitude and Mixpanel, once an event is tracked incorrectly, it's permanently stored. You can't easily rename properties or modify event structures without complex workarounds. With Mitzu, you can adjust your data model, run the new model, refresh Mitzu—and you're done. This flexibility is a major advantage.

That said, Mitzu is still young and not as feature-complete as PostHog. It doesn't yet have all the report types you'd find in a mature tool. But if you already store event data in your warehouse, Mitzu is a strong option to consider.

Tag Managers

Client-Side Tag Managers

For client-side solutions, we can revisit some of the tools already mentioned in the classic analytics category.

Piwik PRO Tag Manager (PL)

Piwik PRO includes a Tag Manager that is feature-wise quite close to Google Tag Manager. It works in a similar way, making it easy for those transitioning from GTM to quickly adapt.

One important point is that you don't have to use Piwik PRO as your analytics tool. You can use Google Analytics or any other system with it.

The main difference compared to GTM is how consent mode is handled. It's not built-in the same way, so you'll need to configure a custom solution. However, there are guides available to help with this.

Matomo Tag Manager (NZ)

Matomo also offers a Tag Manager, which functions similarly to Google Tag Manager.

If you're looking for a self-hosted alternative to GTM, Matomo's Tag Manager is a solid option.

Server-Side Tag Managers

Server-side Tag Management has become quite popular, though in many cases, it's overhyped.

While there are some good use cases, I still believe that for most companies, it's oversold.

European Server-Side Tag Management

There are some European companies offering Google Tag Manager hosting, such as Stape.

However, these don't really count as full-fledged European alternatives, since they still rely on Google's solution.

The only European server-side tag management solution I am aware of is

Jentis (AT)

Jentis has developed a unique approach to the omnipresent sGTM. They follow a different technological approach by mirroring the client-side journeys on the server-side. Their approach to using a pool of IDs (synthetic users) to remove personal identification from ad identifiers, such as the GCLID, while still retaining campaign information, is very interesting.

I hope that at some point, a strong open-source project will emerge in Europe to provide a real alternative—one that allows companies to deploy server-side Tag Management in a way similar to Google Tag Manager.

For now, though, a managed European alternative doesn't exist.

Event data pipelines (CDI)

Event data pipelines, potentially not CDPs. This category is challenging to define because categorizing Segment and Rudderstack as CDPs (as they self-identify) would expand this to an unwieldy category deserving its own post. Therefore, I'm focusing specifically on their event pipeline functionality rather than their CDP aspects.

The core functionality of Segment and Rudderstack involves collecting events from diverse sources including front end, server side, and webhooks. They process this data—transforming it as needed—then proxy it to various destinations, typically marketing platforms. This remains a common and widely implemented use case.

Snowplow (Uk)

The European alternative in this space is Snowplow, which effectively covers similar functionality but with greater strength in data collection. Having existed for quite some time, Snowplow offers arguably the best trackers for various platforms and an excellent event data model for collection purposes.

Recent developments include Snowbridge, which enables forwarding data to other destinations—a capability that wasn't previously core to their offering. This expands Snowplow from primarily event data collection to supporting real-time data distribution when needed.

A significant limitation is that Snowplow is no longer open source. They also discontinued their cloud product, which briefly offered smaller businesses self-service event data pipeline functionality similar to Segment and Rudderstack. Currently, Snowplow operates as an enterprise solution, leaving a gap in alternatives. While some open source packages offer comparable features, no clear dominant solution has emerged to fill this space.

Business Intelligence

The BI market is still largely dominated by Tableau and Power BI for various reasons. But what are the European alternatives? Let's take a look.

Lightdash (UK)

Lightdash is an open-source and managed BI tool that integrates seamlessly with dbt.

If you already have a well-structured dbt workflow, adding Lightdash can create a highly analytics-engineering-friendly setup.

Lightdash stands out because you can define metrics in dbt, and they automatically populate in Lightdash. Everything can be run via the CLI, and they now support dashboards as code, making it even more developer-friendly.

This makes Lightdash a great BI tool for teams that follow modern data engineering practices.

Count (UK)

Count was one of the first BI tools to introduce a free-form, whiteboard-like canvas for data visualization and modeling.

What makes Count unique is that you work on a blank canvas where you can perform calculations, create modeling steps, and build essential business visualizations in the same place.

This is important because you can work visually on your data models (like directly manipulating a lineage graph). It's fantastic for metric trees—offering flexibility in designing and presenting metrics.

If you like working visually, Count is an excellent option.

Steep (SE)

Steep is a newer-generation BI tool that follows a metric-first approach.

I haven't tested it yet, but it's high on my list because metrics are first-class citizens—you define them first, and then build BI reports around them. This approach could make metric management and reporting much easier.

From everything I've seen and heard, Steep looks extremely promising as a European BI alternative.

Supersimple (EE)

Super Simple is another one of the newer BI tools. Besides classic BI functionality, what sets them apart is their strong metric definition capability. You basically have a semantic layer within the tool.

And I would say they really emphasize AI assistance to enable business users to get to specific insights much quicker.

Cloud Data Warehouses

European cloud data warehouse options present an interesting challenge as there is no obvious option. When discussing cloud data warehouses, I'm referring to products like Google's BigQuery, Snowflake, Databricks, and Azure Synapse—analytical databases that leverage cloud capabilities to scale beyond on-premise or single-node compute solutions.

No clear European alternative exists in this space. I researched European cloud providers to investigate their data offerings, as they initially focused primarily on compute services similar to AWS's early days. There are some promising developments: Scaleway, a prominent French cloud provider, has data warehouses on their roadmap, though still in the discovery phase. OVH Cloud has a public roadmap commitment to investigate data warehouse solutions, though details remain limited.

Exasol, a German company with an established data warehouse product, has been around for some time. I worked on a project using Exasol several years ago, but we migrated away due to prohibitive costs. This situation may have changed, but Exasol still appears positioned as an enterprise product without self-service access options.

When extending the European definition to include Israel, Firebolt emerges as a compelling option comparable to BigQuery or Snowflake in capabilities.

For organizations with modest data requirements, deploying a PostgreSQL instance on European cloud providers remains a good option. Despite my tendency to default to BigQuery even for small projects due to its straightforward setup process, PostgreSQL would suffice for many smaller implementations. One disadvantage of PostgreSQL is the continuous instance operation cost versus consumption and storage-based pricing models of Snowflake or BigQuery.

Another potential avenue involves leveraging Iceberg with the S3-compatible storage offered by most European cloud providers. This approach would allow storing CSV or Parquet files and potentially establishing an Iceberg instance on top, creating a data warehouse alternative—but honestly I don't know enough about this kind of setup to give a good judgement here.

For smaller data setups, DuckDB has become central to data setup experimentation in recent years. While typically a single-node solution, some practitioners have deployed DuckDB in cloud environments through creative implementations on compute functions or Lambda services. Mother Duck offers cloud capabilities but, being American, falls outside our European focus.

The complexity of these alternatives indicates the lack of a straightforward European cloud data warehouse solution. So, I am really hoping that this is something that will come to the European cloud platforms sooner than later.

Please let me know about other alternatives I may have overlooked.

Data Integration and Orchestration

Data integration and orchestration—I've just bundled these two together here. While they could technically fall into separate categories, they're often so closely linked that it makes sense to have them side by side.

In the data integration and orchestration space, there are dominant U.S.-based players like Fivetran or Airbyte, and orchestrators like Airflow/Astronomer. You also have newer options like Dagster or Prefect as well. But what about European alternatives?

Keboola (CZ)

One alternative I frequently use is Keboola, which comes from the Czech Republic. Keboola effectively merges data integration and orchestration capabilities. They offer various connectors to easily load your data. Once loaded, you can transform the data right within Keboola and then push it back out to other platforms. It’s a solid European alternative that I like for their simplicity but still open to integrate custom solutions.

Kestra (FR)

In the category of emerging new orchestrators, there is Kestra, founded in France, which got a lot of traction and attention in the last year. Similar to Airflow and Dagster it is also open-source. It's special flavour is the YAML first approach. Pipelines are consequently defined as YAML files, which makes it potentially more approachable for people with less development backgrounds.

Weld (DK)

Then there's Weld, based right next to me in Copenhagen, Denmark. Weld has a similar setup like Keboola combining intregration, transformation and orchestration. In comparision, I would say they focus more simplicity and have fewer options to enhance it with special configurations. On the other hand they integrate more significantly AI-assistant features.

Funnel (SE)

A classic in this category is Funnel.io. Funnel.io has been around for quite a while, initially focusing solely on marketing data integration. Over time, they've expanded significantly to offer what is essentially a comprehensive marketing analytics platform. You can still integrate numerous marketing sources, carry out transformations directly within the platform, and then push your data into various destinations for reporting and visualization.

Supermetrics (FI)

Another classic one in this category. First of all the love child of every technical marketer that wanted a good solution to bring Google ads data into Google Sheets. Today it offers integration, a custom storage and destinations to load the data to.

Each of these European solutions brings something unique to the table, providing strong alternatives to their American counterparts.

Data Transformation

Data transformation? I mean, data transformation can be a vast field with countless approaches. Here, though, I’m focusing on the kind I work with most—SQL transformation.

In this space, dbt is the dominant player, and I’m convinced it will stay on top for a long time thanks to its massive distribution and strong brand. Even with newcomers like SQL Mesh entering the field, it seems unlikely they’ll dislodge dbt unless someone brings something entirely different to the table. At the moment, I just don’t see that happening.

They’re open source, yet their companies are firmly rooted in the US market. As far as I’m aware, there isn’t a direct alternative coming out of Europe. Sure, there’s Dataform—a UK-based company that was acquired by Google and is now part of GCP—but beyond that, a distinctly European option seems to be missing.

Final thoughts

Okay, so this was my attempt to come up with a list of European analytics alternatives. As already said in the beginning, there's no intention to recommend anything to you. There's no intention to introduce a morality category here to say we definitely have to go all-in on European solutions.

I think there are different aspects. First of all, it's always good to know about different kinds of alternatives. Just because maybe something smaller, maybe something with a different kind of angle just fits better to your current setup.

The second thing is something that I learned in Denmark. I grew up in Germany where "made in Germany" was something quite present in my childhood. You could always say, "okay, when it's made in Germany, it must be really high quality." This changed over time just because these standards changed a little bit.

When we moved to Denmark, I was introduced to something slightly different. In Denmark, people emphasize buying locally. Locally means, the first step is you really buy something from the region where you live. The next step is you buy something Danish nationally. And the step afterwards is you buy something from Europe.

In Denmark they make it very visible. You will often see from which region a Danish product actually originates. You will always see a Danish flag everywhere that indicates this comes from Denmark. And now even one of the big grocery store chains introduced a new label to show which products are coming from the EU so that consumers can make a decision based on that.

I really started to appreciate this approach when we moved here. When you support your local economy, you support the place you live. Supporting European data vendors will help them hire more people that will live here, that will pay taxes. In the end, you strengthen your ecosystem and your environment in a small degree.

Again, take the list with a grain of salt. Finally, I had this idea to create the post and then I thought, okay, I will definitely miss out on plenty of other solutions. I have no intention to blow up this post and make it unreadable, so I will keep the post as it is.

I will set up a new directory called "European Analytics." I know there are other directories for European alternatives which are broader (eg. https://european-alternatives.eu).

But this one is really just about data and analytics use cases. When you have a tool and you're headquartered in Europe, just let me know so I can add it. I might send you a survey to fill out some information. In the end, we can have a directory where we can check what's up in the European analytics and data space.