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Description
Haan Petrol Stations Netherlands: Complete Location List with CoordinatesThere are 73 Haan Petrol Stations as of 8 May 2026 in the Netherlands. This fully geocoded dataset provides a clean and comprehensive list of all Haan locations, including full address details, administrative divisions, and precise latitude longitude coordinates for GIS, mapping, and analytical use. Data Integrity & Geospatial Precision: This dataset is built using a robust, proprietary methodology that combines continuous web collection with on
There are 73 Haan Petrol Stations as of 8 May 2026 in the Netherlands. This fully geocoded dataset provides a clean and comprehensive list of all Haan locations, including full address details, administrative divisions, and precise latitude/longitude coordinates for GIS, mapping, and analytical use.
Data Integrity & Geospatial Precision: This dataset is built using a robust, proprietary methodology that combines continuous web collection with on-demand updates to ensure market-leading data freshness. Each location undergoes rigorous, multi-stage validation — including both sophisticated automated filtering and final verification by geospatial analysts — to guarantee maximum precision, reliability, and fitness for professional analytical use.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Admin_level_1
- Admin_level_2
- Settlement
- Region
- Postal Code
- Address
Number of Haan locations per region
- 34 Haan Petrol Stations in Zuid-Holland
- 11 Haan Petrol Stations in Noord-Brabant
- 7 Haan Petrol Stations in Limburg
- 6 Haan Petrol Stations in Gelderland
- 5 Haan Petrol Stations in Utrecht
- 4 Haan Petrol Stations in Noord-Holland
- 2 Haan Petrol Stations in Groningen
- 1 Haan Petrol Stations in Drenthe
- 1 Haan Petrol Stations in Flevoland
- 1 Haan Petrol Stations in Overijssel
- 1 Haan Petrol Stations in Zeeland
Data Preview
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 8048969... | Haan (Alblasserdam) | 51.856851 | 4.667677 | 2952 BC | 1 De Helling, Alblasserdam, 2952 BC, ... |
| 4bd3bb3... | Haan Express (Krimpen aan de Lek) | 51.892743 | 4.628429 | 2931 CE | 21 Hoofdstraat, Krimpen aan de Lek, 2... |
| e1c1f84... | Haan Express (Doenrade) | 50.962927 | 5.903183 | 6439 AA | 82A Provincialeweg Zuid, Doenrade, 64... |
| a94b358... | Haan (Udenhout) | 51.608670 | 5.149471 | 5071 BJ | 114 Kreitenmolenstraat, Udenhout, 507... |
| 10bb763... | Haan (Apeldoorn) | 52.193713 | 5.976264 | 7331 NS | 37 Marchantstraat, Apeldoorn, 7331 NS... |
Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all comprehensive fields and verify the data structure.
Acquire and Evaluate the Haan Location Dataset
The full dataset and a free sample are both available for INSTANT download in a clean, analysis-ready CSV format. Use the free sample to evaluate the structure, fields, and geospatial precision before purchase. This comprehensive data is perfect for geospatial analysis, competitor benchmarking, market studies, site planning, and retail location intelligence workflows.
Learn more about the brand network in our report: View Report
Get a huge discount with our Bundle dataset
For a broader market overview, consider the complete dataset Top 14 Petrol Stations Brands in the Netherlands. This bundle provides a fully standardised, country-wide list of all major chains and is available at a significantly discounted price of €360.
Explore the Top Brands dataset →
Related datasets and resources
- Administrative boundaries and full polygon dataset for the Netherlands: High-precision, ready-to-download boundary polygons covering all administrative levels — ideal for geospatial mapping, territorial analysis, and data enrichment.
- Demographics dataset for the Netherlands (population, households, age, income): Detailed socio-economic indicators at granular geographic levels. Perfect for market sizing, modelling, demand forecasting, and neighbourhood-level insights.
- Explore demographics data insights for the Netherlands: Methodology, use cases, definitions, and examples explaining how to use demographic and geospatial datasets for analysis and decision-making.
- Income indicators dataset for the Netherlands (small-area income analysis): Download a comprehensive dataset on income distribution across small geographic units — ideal for segmentation, customer analytics, location planning, and socio-economic scoring.
- Income distribution and socio-economic patterns in the Netherlands — expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
- Explore a rich library of the Netherlands-specific datasets on our dedicated country page: detailed demographics, high-resolution wealth and income indicators, multi-level administrative boundaries, and a broad spectrum of Points of Interest including major brands and retail locations — all designed to power market analysis, spatial planning, and location intelligence. View datasets for the Netherlands
Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at [email protected].
Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.
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4.3 ★★★★★
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Product Reviews
★★★★★ 3
have some good contents but too general
Format: Paperback
The book covers some good points, but overall, it's too general.
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Reviewed in the United States on June 28, 2024
★★★★★ 3
Why Politics in a Tech Book????
Format: Kindle
Well... I'm surprised to see the book blatently calls out its dedication to Black Lives Matter, which is in all caps so I assume it's referring to the political organization. It goes on to speak of 2020 being the year of an "awakening of injustices of systematic racism"... I thought I was buying a technical book??? Had I known this political bs was included I wouldn't have purchased it! However, I bought and I'm still reading it. If the politics goes away and the TECHNICAL content is good I'll update my review.
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Reviewed in the United States on December 13, 2020
★★★★★ 2
Not good use of time
Format: Paperback
It’s not clear who this book targets - neither experts nor novice will benefit. There are expert perspectives, only few of these are helpful, rest are too generic to be of any use. For instance the last entry is one an engineer who shares how she went from zero to expert in cloud engineering in six months but fails to mention a single resource or pathway for others to follow.
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Reviewed in the United States on April 2, 2022
★★★★★ 3
Uneven compendium of tips and insights, but still very useful
Format: Kindle, Format: Kindle
“In theory, theory and practice are the same. In practice, they are not" is why such bottom-up insights and lessons from the field are the fastest way to learn real life stuff. This series had a GREAT start with "Engineering Management" - I guess because it is way more subjective than Cloud Engineering and offered a variety of non-overlapping POVs. This one is a mixed bag, perhaps because "Cloud Engineering" was perceived amorphously by the authors. The scope was broad - from cloud-native (architecture), to cloud-ready (topology), to cloud-operations, to choosing tech (e.g., Lambda/serverless), to -ilities and economics -- it is like celebrating Halloween, Christmas and Labor Day together in a single long weekend.
I would give it 4/+ stars if at least 25% of such a book was "superb", giving 3 because about 10% of the book is. That still leaves 10 solid insights or learning that would otherwise take many failures to learn. And failures, especially in this emerging domain of complexity, is VERY expensive. Would love to see more books like this.
Let's summarize some key insights -
-- Real-time visibility across the entire DevOps lifecycle is key to winning in cloud.
-- Operations, especially operations at scale, is extremely hard. So, wherever possible, use Managed Services.
-- Distinguish between "availability" and "uptime" and measure each separately, and concretely.
-- In FaaS/Serverless, calling a function synchronously increases debugging complexity.
-- Good code is like good joke - it needs no explanation.
-- "Building your app or platform on top of the abstractions that a cloud provider gives you does not make the underlying layers stop existing. In many cases, it makes them even more important." That makes the failure modes LESS obvious than we were used to. Therefore having "extreme visibility" into your systems will help "separate the issues at the layer you're focused on from the fundamental system issues". i.e., just because what was under the hood is now even less visible, don't forget them. Many recent "cloud failures" have been in networking fault domains.
-- Cloud is not optimized for replacing static infrastructures.
-- Containers, service meshes and serverless jumpstart dev productivity but they also change the attack surface of apps and infra.
-- "Number of containers that are alive for 10 sec or less has doubled to 22%". 73% of all containers live for 30 minutes or less.
-- Adopt an "assume breach" stance for everything. Have a break-glass account.
-- Ensure you have a thorough understanding of where and how secrets are secured.
-- Grey failures (transient degradation of services) are often worse than complete crashes, since the latter have a short feedback loop.
-- Resilience engineering has existed as a sub-discipline within safety sciences. We just recently started applying its concepts in technology. Resilience can be thought of as a "socio-technical system" with Robustness ("system X has property Y that is robust in sense Z to perturbation W"); Reliability (consistent operations or service levels); Rebound (ability to deal with a chaotic situation using structures developed AND deployed BEFORE the chaos). In other words, robustness protects systems against a SPECIFIC type of failure mode. When a system is robust in many dimensions, it approaches good resilience to failure.
-- Resilience is something you "do", not something you "have". Resilience is a verb.
-- Moving from one class of nines to the next is 10 times more expensive.
-- Production System really means "system that someone else, anyone else, can hold you accountable for".
-- Most common theme across incidents is that something, somewhere was surprising.
-- Incidents are unplanned investments...your challenge is to maximize ROI.
-- We used to think of scale in two dimensions - horizontal (more) and vertical (bigger). In cloud, think of "scale out" (when demands increase) and "scale in" (when demand decreases).
-- Architecture diagram is also a map of failure modes.
-- Async communication is a friend of Cloud Reliability.
-- Test in production is a competitive advantage. The complexity of traffic patterns going through high-scale production systems is increasingly harder to reproduce in a controlled env.
-- Hundreds of open issues is fine, but if the repo has gone months (or, years!) without a release, THAT is a warning sign.
-- It is hard to write good tests for bad code.
-- Platforms come and go. But first principles and patterns will always exist, because they are the ones and zeros.
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Reviewed in the United States on November 6, 2023
★★★★★ 2
Shallow, biased and significantly overpriced
Format: Paperback
Well, this purchase was a disappointment. 20% of the pages are dedicated to just highlighting the bios and backgrounds of the many different authors that contributed this great wisdom. And let me be clear, the authors are solid. They are professionals with credible backgrounds and experience. But it's the format and constraints of this book that makes it virtually impossible for that to shine through. Because the rest of the book (80%) is dedicated to the so called "97 things every cloud engineer should know". And unfortunately the average length of one of these "things" is about 1.5 pages long, and as such extremely shallow and in about 30% of the cases straight up promotions for specific company services. You will find Google cloud advocates telling you to use managed services, of Google of course. AWS engineers telling you to avoid them and use IaaS. LaunchDarkly employees telling you to use feature flags. The list goes on. The TL;DR: here is that if you have built anything on the cloud in the last 2 years, this book is going to be a waste of your time and money. You are better of googling: "cloud best practices" and dedicating 2h to reading the first 10 non-ad related search results.
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Reviewed in the United States on March 23, 2022