NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms
Berlin had the highest guest nights in short-stay rentals booked through online platforms of 394 areas in 2019, at 4.22 million. Frankenthal (Pfalz), Kreisfreie Stadt had the lowest, at 907. The median was 34,230 and the figure for Germany was 37.24 million. Source: Eurostat, European Commission.
Top 40 areas, 2019
Full ranking
Other periods
About this ranking
Nights spent by guests, residents of the country and visitors from abroad together, in short-stay accommodation (NACE Rev. 2 group 55.2: holiday flats, houses and rooms) booked through Airbnb, Booking or Expedia, from booking data the platforms share with Eurostat. Every guest counts: a family of four staying three nights is 12 guest nights.
Official statistics compiled by Eurostat from data the platforms transmit under agreements with the European Commission, published only as totals across platforms. Data start in 2018. Tripadvisor also reported until 2024; Eurostat found no break when it left. Hotels listed on the platforms are not included. Do not add these nights to tourist_nights: national accommodation surveys already count some of the same rentals. Eurostat withholds NUTS 3 values where few bookings would reveal individual hosts.
Every value in the ranking comes from the same publisher and the same period, so the areas are compared on one definition. 6 areas with data in other periods have no value for 2019 and are left out rather than filled from another source. Equal values share a rank.
How to cite
Eurostat. Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3). https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table. Retrieved 2026-10-12.Citation styles
APA 7
Eurostat, European Commission. (2026). Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3) (NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019) [Data set]. Retrieved October 12, 2026, from https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table
MLA 9
Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3), NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019. Eurostat, European Commission, 22 Sept. 2026, https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table. Invokely, https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019. Accessed 12 Oct. 2026.
Chicago (author-date)
Eurostat, European Commission. 2026. Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3). NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019. Dataset. Accessed October 12, 2026. https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table. Also distributed by Invokely, https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019.
Harvard
Eurostat, European Commission (2026) Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3), NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019 [Dataset]. Available at: https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table, via Invokely: https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019 (Accessed: 12 October 2026).
BibTeX
@misc{eurostat_nuts_3_areas_of_2019,
author = {{Eurostat, European Commission}},
title = {{Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour\_ce\_oan3): NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019}},
year = {2026},
howpublished = {Data set},
url = {https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table},
urldate = {2026-10-12},
note = {Accessed via Invokely, https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019. Publisher attribution: Eurostat. Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour\_ce\_oan3). https://ec.europa.eu/eurostat/databrowser/view/tour\_ce\_oan3/default/table. Retrieved 2026-10-12.},
}
RIS
TY - DATA
AU - Eurostat, European Commission
TI - Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3): NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms, 2019
PY - 2026
DA - 2026/09/22
PB - Eurostat, European Commission
DB - Invokely
UR - https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table
L2 - https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019
Y2 - 2026/10/12
N1 - Accessed via Invokely, https://invokely.ai/rankings/short-stay-platform-guest-nights/germany-provinces?period=2019.
N1 - Publisher attribution: Eurostat. Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3). https://ec.europa.eu/eurostat/databrowser/view/tour_ce_oan3/default/table. Retrieved 2026-10-12.
ER -
Use this data in your AI agent
Invokely serves this figure to AI assistants through MCP and to code through a REST API, with the source and citation attached. Ask your assistant:
Rank NUTS 3 areas of Germany by guest nights in short-stay rentals booked through online platforms using official data, and cite the source.
rank_places {"indicator":"short_stay_platform_guest_nights","level":"province","within":"Germany","limit":10}
GET https://invokely.ai/api/v1/rank?indicator=short_stay_platform_guest_nights&level=province&within=Germany&limit=10Questions
Which area has the highest guest nights in short-stay rentals booked through online platforms?
Berlin, with 4.22 million in 2019, according to Eurostat, European Commission.
Which area has the lowest guest nights in short-stay rentals booked through online platforms?
Frankenthal (Pfalz), Kreisfreie Stadt, with 907 in 2019.
Where does this ranking come from?
Every value comes from one source and one period, so the places are comparable: Eurostat, European Commission, Guest nights spent at short-stay accommodation offered via online platforms by NUTS 3 region, residents and non-residents (tour_ce_oan3). Retrieved 2026-10-12. 6 areas have no value for 2019 and are not ranked.