Gastro Report · Zurich · Updated 2026-06-28

Zurich at the Table — 2,860 gastro places across 18 subtypes

This report is a map-first directory drawn from Localinar's per-city dataset for Zurich (version 1.0, 2026-06-28, 12,497 total entities). Every figure on this page is either a count, a coordinate, or a name pulled directly from the dataset. There are no ratings, no prices, no opening hours and no quality judgements — only what the dataset actually contains. Coverage varies — some businesses may not yet be on our map.

2,860
Gastro-related entities
18
Distinct subtypes
3,041
Food & Hospitality (top-level)
12,497
Total entities in dataset
Coverage

A 14.4 × 14.9 km footprint at ~13.25 places per km²

The 2,860 gastro entities sit inside a bounding box that stretches from lat 47.320029 to 47.450083 (north–south) and from lon 8.450252 to 8.649195 (east–west). That is roughly 14.44 km north-to-south by 14.95 km east-to-west — and within that footprint the dataset carries an approximate density of 13.25 gastro places per square kilometre. For comparison, the cycling layer of the same dataset covers a similar area at roughly 0.6 entities per km² — about 22× sparser than gastro.

Bounding box
lat  47.320029 → 47.450083  (~14.44 km N–S)
lon  8.450252 → 8.649195  (~14.95 km E–W)
density  ~13.25 entities / km²

The footprint extends beyond Stadt Zürich into surrounding municipalities such as Küsnacht, Opfikon and Dübendorf. The dataset's Kreis label only applies to City-of-Zurich entities, so places outside the city carry no district value — a known limit, not a defect.

Top tier · the Big Four

Restaurant 1,342 · Cafe 412 · Fast Food 406 · Bar 246

Together these four subtypes account for 2,406 of the 2,860 gastro entries — roughly 84% of the layer. Each card below shows the count, the keyword(s) that matched against the sub/subEn field, and a list of named entities pulled verbatim from the dataset.

Restaurant

keywords matched: restaurant
1,342
The single largest gastro bucket. Cuisine is not a field in the dataset, so Asian, Italian, Swiss and everything else all sit inside this one count.
  • Asia Lena Take Away47.370915, 8.638791
  • Asia Lena Take Away site↗ external
  • Asian fusion by Suan Long47.39744, 8.618168
  • Auenstube · site47.441704, 8.625999
  • Bahnhöfli · site47.399461, 8.621417
  • Bamboo · site47.408817, 8.640637
  • Bistro Hà Nôi47.398554, 8.617902
  • Bistro Racket · site47.378183, 8.645334
  • Bistro Sunnetal47.371027, 8.643593
See all 1,342 restaurants on the map →

Cafe

matched: cafe
412
  • Ambiente47.400127, 8.622671
  • Bistro am Südplatz · site47.449259, 8.566663
  • Bistro im Spilhöfler47.369657, 8.455292
See all 412 cafes →

Fast Food

matched: fast food
406
  • Adam's Döner47.41243, 8.620426
  • Alussia · site47.446139, 8.579627
  • Barnabas · site47.429164, 8.467611
  • Bahnhof Imbiss47.399933, 8.623662
See all 406 fast food →

Bar

matched: bar
246
  • Bar 547.431496, 8.468519
  • Bar Iris · site47.449804, 8.56549
  • Bar Snatch · site47.322522, 8.532035
See all 246 bars →
Mid tier

Pub 116 · Bakery 106 · Wine Shop 52 · Delicatessen 52

The next-largest subtypes. Each card shows count, matched keywords, and at least one named example with coordinates from the Localinar dataset.

Pub

matched: pub
116
  • Bücherwagen47.326121, 8.514242
See all on the map →

Bakery

matched: bakery
106
  • Beck von Burg47.346446, 8.600186
  • Bode Bäckerei-Konditorei · site47.326934, 8.489843
See all on the map →

Wine Shop

matched: wine
52
  • Andys Weingenuss · site47.396161, 8.617141
See all on the map →

Delicatessen

matched: deli, delicatessen
52
  • Casa Mediterranea47.37164, 8.639622
See all on the map →
Specialty

Ice Cream 26 · Food Court 22 · Coffee 21 · Drinks 21

Mid-volume specialty subtypes. Counts are exact; named examples come straight from the Localinar dataset.

Ice Cream

matched: ice cream, gelateria
26
  • Gelateria Veneziana47.396653, 8.625277

Food Court

matched: food
22
  • Mensa47.324064, 8.471731

Coffee

matched: coffee
21
  • Café etc · site47.39642, 8.62947

Drinks

matched: drinks
21
  • Hedinger Wein & Mode · site47.368466, 8.545652
Long tail

Confectionery 14 · Brewery 9 · Tea 9 · Beer Garden 3 · Snacks 2 · Confiserie 1

The smallest gastro subtypes by count. Each card lists the matched keywords and named entities. Counts are keyword-matches against the subtype label — so a brewery tagged as "Pub" or "Restaurant" in the Localinar dataset would not appear in the Brewery card here.

Confectionery

matched: confectionery, konditorei
14
  • autPartners · site47.321757, 8.521943

Brewery

matched: brewery
9
  • Rümlanger Brauwerkstatt · site47.445914, 8.539191
  • AMIV Bräu Braukommission · site47.37879, 8.549321
  • Brauerei Hardwald AG · site47.403794, 8.602952
  • Brewdaz · site47.382396, 8.513608
  • Hirnibräu · site47.400075, 8.532185
  • Turbinenbräu · site47.384266, 8.496514

Tea

matched: tea
9
  • London Tea · site47.374916, 8.536613
  • Paper & Tea · site47.373372, 8.539455
  • Shui Tang · site47.372267, 8.545621

Beer Garden

matched: beer, garden
3
  • Hop Up Hardwald · site47.403623, 8.602696

Snacks

matched: snacks
2
  • Pinguin-Hüsli47.384933, 8.574842
  • Trampeltier-Kiosk47.386601, 8.574052

Confiserie

matched: confiserie, konditorei
1
  • named entity not surfaced in sample
Honesty

What this dataset cannot tell you

Plainly: the gastro directory is an inventory of places, not a guidebook. The fields below are absent from every entry. Treat the limits as the boundary of an inventory, not a defect.

Cuisine is not a field. Asia Lena Take Away (subtype: Restaurant), Bistro Hà Nôi (subtype: Restaurant) and Bamboo (subtype: Restaurant) all sit inside the same Restaurant bucket of 1,342 entries. There is no single-bucket cuisine split.

Partnership is a flag, not a contract. The dataset carries a Yes/No-style partnership marker — but no contract terms, fees, or partner-onboarding dates.

And, listed verbatim, these are the things the dataset does not contain:

  • The dataset does not include opening dates, founding years, or any historical/time-series data for entities.
  • There are no price levels, average bills, or cost-tier indicators for any business.
  • There are no quality ratings, review counts, star ratings, or popularity scores.
  • There are no employee counts, revenue figures, or other firmographic data.
  • There are no opening hours, closure status, seasonal indicators, or operational schedules.
  • There are no city-level metrics such as municipal budgets, modal-split percentages, transport plan targets, or population figures.
  • No demographic data (age, income, household size) for the catchment areas around any entity.
  • Bicycle infrastructure is NOT directly captured: there are no entries for bicycle parking, bike rental stations, dedicated bike-repair workshops as a subtype, e-bike charging points, or cycle paths/lanes as features.
  • There is no explicit 'cycling infrastructure' or 'bicycle parking' subtype — the 120 cycling-related entities are overwhelmingly retail (Bicycle Shop = 116).
  • Although the field 'district' (Kreis) is present on 11,023 of 12,497 entities (88.2%), 1,474 entities (11.8%) lack a district assignment, and the values are limited to City of Zurich Kreise — entities in surrounding municipalities (e.g. Küsnacht, Opfikon, Dübendorf, Regensdorf) do not carry a district label.
  • 20 of 12,497 entities are missing lat/lon coordinates and cannot be mapped.
  • 5,123 of 12,497 entities (41.0%) have no url field, meaning many businesses have no linkable website in the dataset.
  • Only 20 entities have free-text descriptions; for everything else the only descriptive text is the name and the subtype label.
  • There is no field indicating which entities accept tourists vs locals, language(s) spoken, accessibility features, payment methods, takeaway/delivery options, or any other service attributes.
  • There is no temperature, weather, elevation, terrain, or topographic data attached to any entity.
  • Partnership values are limited (Yes/No-style flag) and the dataset does not disclose contract terms, fees, or partner-onboarding dates.
Methodology

How these counts were derived

Counts are derived from the Localinar entity database for Zurich as of 2026-06-28. The snapshot used here is the Localinar dataset (version 1.0, 2026-06-28), containing 12,497 entities. Subtype labels come from our standardised taxonomy.

  • Each entity carries a name, a top-level category, a native-language subtype, an English subtype, and a partnership flag. Coordinates are present on 12,477 of 12,497 entries.
  • Subtype counts are derived by string-matching keywords against the subtype labels — e.g. the Brewery count of 9 matches the keyword "brewery". This means an entity labelled "Pub" in the dataset would not be counted in Brewery even if it brews on-site.
  • Top-level Food & Hospitality totals 3,041; the gastro layer reported here is 2,860 of those, the difference being entries whose subtype does not match any of the 18 gastro keywords used (e.g. unclassified Food & Hospitality entries).
  • Taxonomy coverage is uneven — only 20 of 12,497 entities carry free-text descriptions, and website coverage is 59% (7,374 of 12,497). Coverage varies — some businesses may not yet be on our map.
  • The Kreis ("district") field applies only to City of Zurich. Entities in Küsnacht, Opfikon, Dübendorf and other surrounding municipalities carry no district value — this is a known property of the dataset, not a derivation error.
FAQ

Honest answers

How many gastro places are in this dataset?
2,860 gastro-related entities across 18 distinct subtypes, sitting inside a top-level Food & Hospitality bucket of 3,041. Every count on this page is a direct projection of the dataset as of 2026-06-28.
Why don't you show ratings or prices?
Because the dataset does not contain them. There are no review counts, star ratings, popularity scores, price tiers or average-bill figures attached to any entry. Adding such labels would be a fabrication.
Why is there only one Restaurant subtype for 1,342 places?
Cuisine is not a field in the dataset. Asia Lena Take Away, Bistro Hà Nôi and Bamboo are all labelled "Restaurant" in the dataset. We respect that and do not invent cuisine tags.
Does this cover only Stadt Zürich?
No. The bounding box of 47.32–47.45 N and 8.45–8.65 E covers ~14.4 × 14.9 km and includes surrounding municipalities such as Küsnacht, Opfikon and Dübendorf. However the Kreis district label only applies to City-of-Zurich entries.
How do you decide which entity is a "Brewery"?
A simple keyword match against the subtype label. The brewery count of 9 reflects entities whose subtype label matches "brewery" — places that brew but are tagged as Pub or Restaurant won't show up here.
Can I see these on a map?
Yes — every card carries a "See on the map" link to the Localinar Zurich Stadtkarte filtered by that subtype.
How to read this

Where these 2,860 places sit in the wider dataset

The full Zurich file holds 12,497 entities across six top-level categories. Gastro (2,860) and Cycling (120) are two of many layers we publish.

Commercial & Retail

5,551

Food & Hospitality

3,041

Public & Institutional

1,768

Sports & Recreation

1,053

Social & Community

548

Culture & Events

536

Fields always present on every entity: name, top-level category, native-language subtype, English subtype, partnership flag. Sometimes missing: coordinates, website, district, free-text description. Coverage: coordinates on 12,477 of 12,497; websites on 7,374 of 12,497 (59%); district on 11,023 of 12,497 (88.2%); free-text descriptions on only 20 entries.

Provenance: bounding box ~47.32–47.45 N, ~8.45–8.65 E. Source: the Localinar dataset (version 1.0, 2026-06-28).

Related

More views of the Localinar dataset, in Zurich and beyond.