Swiggy Dataset
Live and Historical Data Across India’s Delivery-First Food Ordering Platform
Swiggy built its reputation on delivery speed and reliability first, restaurant discovery second — unlike a platform that scores a restaurant separately for dine-in and delivery experience, Swiggy’s rating largely reflects the ordering-and-delivery journey itself, since that’s overwhelmingly how people use the app. Layer on Swiggy One, a single membership that spans food delivery, Instamart grocery, and Dineout under one subscription rather than separate loyalty tiers, and pricing on a given restaurant listing can quietly include a membership-linked discount that a simple menu scrape would never catch.
Tracking that properly means capturing live delivery-time performance and Swiggy One-linked pricing as first-class fields, not afterthoughts bolted onto a generic restaurant-listing crawl. That’s exactly what our dedicated Food Delivery Data Scraping pipeline is built to handle for Swiggy specifically — a Swiggy Food Delivery Dataset that ties menu pricing, ratings, delivery-time data, and customer reviews together at the restaurant and item level, refreshed on a schedule you control. It sits inside our broader Food Delivery Dataset catalog, built on the same infrastructure as our Food Delivery Data Scraping services, with custom builds available through our Web Scraping Services team.
Request Free Sample DatasetQuick Stats
Price From
$189Starting Price
Records
2.9M+Total Records
Format
CSV / JSONDelivery Format
Delivery
ImmediateAvailability
15+
Cuisine Categories
2+ Yrs
Historical Depth
Pan-India
City Coverage
Daily
Refresh Cycle
Why Teams Choose Our Swiggy Dataset Over a DIY Crawl
Swiggy One membership pricing doesn’t show up on a plain menu-price scrape, and live delivery-time performance is one of the platform’s most closely watched metrics internally — a scraper that only checks price and rating once a day misses both.
One Schema, Every Data Layer
Restaurant metadata, menu items, prices, ratings, and delivery-time estimates all arrive in a single Swiggy dataset — no reconciling separate exports.
Item-Level Menu Precision
Our Swiggy Menu Dataset tracks individual dish pricing and availability, not just a restaurant-level price band, so category-level food-cost comparisons are actually possible.
Scoped to What You Actually Need
Pull specific cities, cuisines, or the full restaurant catalog. Refresh daily, weekly, or near-live. Delivered as CSV, JSON, Excel, or a direct API feed.
Formats Your Tools Already Read
CSV and Excel exports work straight in Power BI or Tableau. JSON and API feeds ship with a documented schema for Snowflake, BigQuery, or Redshift.
Live Data, Plus Real History
See today’s menu prices and delivery times alongside 2+ years of historical rating and pricing trends across restaurants.
Delivery-Time Performance Tracked Closely
Coverage treats delivery-time and ETA accuracy as a core signal, reflecting how central speed is to Swiggy’s own positioning and ranking logic.
What’s Actually Inside the Swiggy Dataset
The Swiggy dataset answers five practical questions: what a restaurant serves, what it costs, how it’s rated, how fast it delivers, and what customers actually say about the experience. Those five questions map to the five sub-datasets described below, all keyed together on a common restaurant and item identifier.
Most clients start with delivery-time and pricing together, usually chasing a specific question — does a restaurant’s Swiggy One-linked discount meaningfully change its effective menu price, or how does delivery-time performance for a given cuisine compare across competing platforms in the same city? Brand and franchise teams lean on the ratings layer to catch a quality dip early, since it tends to show up in Swiggy’s rating trend before it shows up in order-volume reports. Data teams mostly just want clean, timestamped records instead of raw page data, which is really the core value of buying a dataset instead of building a scraper from scratch. This dataset shares its collection standards with our broader Food Delivery Dataset catalog.
What people actually build with Swiggy Food Delivery Dataset:
- Menu-pricing benchmarking: Compare item-level pricing for a given cuisine or dish type across competing restaurants in the same city.
- Delivery-time and ETA benchmarking: Track how delivery-time estimates vary by city, cuisine, and time of day, and how they compare to competing platforms.
- Swiggy One impact tracking: Measure how membership-linked discounts affect effective menu pricing across restaurants.
- Rating-trend monitoring: Catch quality dips early by tracking rating movement before it shows up in order volume.
- Sentiment research: Mine the Swiggy Customer Reviews Dataset for recurring complaints about food quality, packaging, or delivery timing.
Key Metrics
Price
$189.00Format
CSV / JSON / APIRecords
2.9M+ Verified RecordsCoverage
Pan-IndiaUpdate Frequency
DailyAvailability
Instant AccessDelivery Time
ImmediatelyPreview actual dataset structure before purchase.
A Sample of the Swiggy Dataset
Below is a small, illustrative slice of a single extract. Each row represents one menu-item observation with commercial and rating attributes captured at a point in time. Over 45 additional fields are available, including cost-for-two data, cuisine tags, and full price-history timestamps.
| Restaurant Name | Restaurant Image | Cuisine | Discount | Max Discount | Delivery Time | Rating | Location |
|---|---|---|---|---|---|---|---|
| Pizza Hut | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2026/6/15/82d754e9-c41a-46a1-bbd0-a2b2fc0aa0dd_47589.JPG | Pizzas | 50% OFF | 20-25 mins | 4.1 | Ashram Road | |
| Barbeque Nation | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/izngkxnhvcxpw0y3dgvt | North Indian, Barbecue, Kebabs, Biryani, Street Food, Snacks | 70% OFF | ₹140 | 40-50 mins | 4.1 | Vastrapur |
| Chinese Wok | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/e0839ff574213e6f35b3899ebf1fc597 | Chinese, Asian, Tibetan, Desserts | 70% OFF | ₹140 | 20-25 mins | 4.2 | CG Road |
| Burger Farm | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/9/10/7c88c53b-c0e9-45da-a86a-6f0e04af6777_765502.JPG | Burgers, American, Barbecue, Italian-American, Snacks, Grill, Beverages, North Indian | 70% OFF | ₹140 | 20-25 mins | 4.5 | Maninagar |
| Super Dawat Tawa Fry Centre | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/ye0cuamd3narriqobmrq | North Indian, Tandoor, Biryani, Seafood | 10-15 mins | 4.0 | Navrangpura | ||
| Burger King | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/6/18/213f6e83-e923-4c30-bd12-ebf12aa61ad3_81814.jpg | Burgers, American, Salads, Beverages, Chaat | 15-20 mins | 4.2 | CG Road | ||
| McDonald's | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2026/6/18/4e67ed9b-ccdc-4cf6-ab18-a2093f54bc43_52630.JPG | Burgers, Beverages, Cafe, Desserts | 30% OFF | ₹70 | 10-15 mins | 4.3 | Ashram Road |
| The Belgian Waffle Co. | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/6/16/37304e49-58ca-4c4c-a772-46381af2dc51_324540.jpg | Waffle, Desserts, Ice Cream, Beverages | 20-25 mins | 4.5 | Shahibag | ||
| Subway | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2025/6/12/ced79013-b55e-4ed5-aa79-bd22b4c14706_40831.jpg | sandwich, Salads, wrap, Healthy Food | 10-15 mins | 4.5 | Navrangpura | ||
| KFC | https://media-assets.swiggy.com/swiggy/image/upload/fl_lossy,f_auto,q_auto,w_660/RX_THUMBNAIL/IMAGES/VENDOR/2026/7/1/178a63d5-5676-4621-baac-ca031513ec67_395939.JPG | Burgers, Fast Food, Rolls & Wraps | 50% OFF | 20-25 mins | 4.0 | Paldi & Ambawadi |
The Five Layers of the Swiggy Dataset
Rather than one flat export, the Swiggy dataset splits into five connected layers, licensed individually or together as a complete Swiggy Food Delivery Dataset, joined on a common restaurant and item key.
Swiggy Menu Dataset
The descriptive layer behind every dish a restaurant lists — what it is, how it’s categorized, and how it’s presented to customers browsing the app.
- Menu item name, category (starters, mains, desserts, beverages), and cuisine tags
- Description text, portion size, and dietary flags (veg, non-veg, vegan, jain)
- Item image URLs where available
- Combo and meal-deal configuration where applicable
Swiggy Price Dataset
Menu pricing on Swiggy can shift with delivery-fee structure and Swiggy One membership benefits, which apply across food delivery, Instamart, and Dineout rather than sitting in a separate loyalty program.
- Item-level price, cost-for-two estimate, and delivery-fee data by restaurant
- Full price-change history with timestamps
- Swiggy One discount and free-delivery flags tied to their active window
- Packaging-fee and platform-fee data where separately itemized
Swiggy Ratings Dataset
Because Swiggy’s core experience is delivery-first, its restaurant rating largely reflects the ordering-and-delivery journey rather than splitting into separate dine-in and delivery scores.
- Overall restaurant rating and rating-count data for statistical confidence
- Rating-distribution data by star level
- Historical rating trends to detect quality shifts over time
- Category-level rating benchmarks by cuisine and city
Swiggy Delivery Dataset
Delivery-time performance sits close to the center of Swiggy’s product and ranking logic, making this one of the most closely watched data layers on the platform.
- Average and real-time delivery-time estimates by restaurant and area
- Delivery-radius and serviceable-area data
- Order-acceptance and preparation-time signals where available
- Historical delivery-time trends by city and time of day
Swiggy Customer Reviews Dataset
Star ratings tell you something went wrong; written reviews tell you what. This layer keeps the detail instead of collapsing everything into an average.
- Individual reviews with rating, review text, and submission date
- Verified-order flag and anonymized reviewer identifier
- Aspect-level sentiment: food quality, packaging, delivery timing, and value for money
- Review-velocity trends useful for catching a quality issue before it shows up in order volume
Where the Swiggy Dataset Runs Deepest
Swiggy’s restaurant network spans the full breadth of Indian dining culture, from metro fine-dining to tier 2 and tier 3 city cloud kitchens, so our coverage reflects that same spread.
North Indian & Mughlai
Deepest historical depth and highest order volume across metro cities.
Chinese & Fast Food
High-frequency reorder category with strong delivery-time sensitivity.
Cloud Kitchens
Delivery-only brands tracked distinctly from dine-in restaurants for accurate benchmarking.
Cafes & Beverages
High-frequency reorder category with strong Swiggy One promotional activity.
Add-Ons
Swiggy One pricing differentials, cloud-kitchen-specific tracking, and festive-season demand archives.
How Different Teams Put This Dataset to Work
The same underlying dataset ends up solving fairly different problems depending on who’s using it.
Competitive Menu Pricing
Track how competing restaurants price the same dish category across cities, instead of manually checking listings.
Franchise Performance Monitoring
Compare ratings and delivery-time performance across franchise locations to spot underperforming outlets early.
Food Delivery Market Research
Use multi-year rating and pricing history to understand how cuisine trends and delivery expectations are evolving.
Delivery-Time Benchmarking
Analyze delivery-time patterns by city and cuisine to understand where fulfillment speed is a competitive advantage.
AI and LLM Training Data
Use the clean, labeled Swiggy Menu Dataset as training data for menu-item extraction and food-recommendation models.
Sentiment and Quality Research
Mine review-level data to understand what drives rating movement for specific restaurant types and cuisines.
Who Actually Uses the Swiggy Dataset
The Swiggy Dataset provides valuable food delivery and restaurant data for market research, competitive analysis, pricing insights, and data-driven business decisions.
Restaurant Chains & Franchises
Benchmark menu pricing and ratings against competitors in the same cuisine and city.
Cloud Kitchen Operators
Track delivery-only competitor pricing and rating performance to refine their own menu strategy.
AI & ML Companies
Source clean, structured food-delivery data for recommendation engines and menu-understanding models.
Market Research Firms
Build category reports on India’s food delivery sector using multi-year historical depth.
Restaurant Consulting Firms
Validate menu-pricing and positioning recommendations with verified, current data.
Investment & Analyst Teams
Track cuisine trends and delivery-time performance as alternative-data signals on the food delivery sector.
What This Dataset Actually Saves You
Manually tracking menu prices, ratings, and delivery times across hundreds of restaurants isn’t realistic without automation — and it definitely won’t catch a same-day menu price change or a sudden dip in delivery-time performance before it affects order volume.
Hours Back, Not Days
A structured feed replaces manual menu-checking entirely — what used to take a team days to compile is available on a schedule you set.
Forecasts Grounded in Real History
2+ years of price and rating data lets you separate genuine quality shifts from short-term promotional noise.
Catching Issues Before They Show Up in Orders
A slip in delivery-time performance or rating often precedes a drop in order volume. A same-day feed means you catch the signal early enough to act.
Built Around Your Pipeline, Not Ours
Pick the cities, cuisines, and cadence that matter to you — delivered as CSV, JSON, API, or Parquet.
How the Swiggy Data Collection Pipeline Actually Works
Here’s the straightforward version of how this gets built, not a marketing summary of it.
Collection Approach
Ethical, rate-limited collection from Swiggy’s publicly visible pages — no credential bypass, no restricted API access.
Validation Before Delivery
Every batch runs through automated schema checks, then a manual spot-check pass before it ships.
Deduplication
Repeat pulls of the same restaurant or menu item are collapsed into one clean historical record instead of duplicate rows.
Refresh Scheduling
Daily, weekly, or intraday cycles keep pricing, ratings, and delivery-time fields current without you having to request a re-pull.
Stable Schema
Field names and structure stay consistent release over release, so your ingestion pipeline doesn’t break on the next refresh.
Compliance
Only publicly available platform data is collected, consistent with standard commercial data practice and platform terms.
This methodology runs on the same Food Delivery Data Scraping infrastructure behind our other restaurant-platform datasets — it’s a maintained pipeline, not a one-off project.
Delivered However Your Stack Expects It
Access the Swiggy Dataset in flexible formats with delivery options designed for seamless integration into your existing systems, analytics tools, and data workflows.
CSV / Excel
Drop straight into Excel pricing models, Tableau dashboards, or Power BI reports.
JSON / API Feed
Documented schema, ready for direct ingestion into your application backend or data pipeline.
Cloud Storage / Database
Automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever cadence you set.
Pick the Plan That Matches Your Scope
Choose flexible Swiggy Dataset pricing plans tailored to your data volume, update frequency, and business requirements.
One-Time Dataset Purchase
From $189
A one-time Swiggy dataset snapshot, delivered right away — no subscription commitment.
What’s included:
- Full point-in-time dataset snapshot
- CSV, JSON, or Parquet delivery
- Filter by city and cuisine before delivery
Enterprise License
Contact Sales
Full-category, pan-India coverage with unlimited access and an SLA behind it.
What’s included:
- Unlimited API calls and delivery volume
- Dedicated account manager, 99.5% SLA
- Custom schema design and white-label delivery
A Team That’s Actually Built This Before
WebDataInsights delivers reliable Swiggy Dataset solutions with accurate food delivery data and scalable delivery for market research, analytics, and competitive intelligence.
Track Record at Scale
Millions of verified records collected and refreshed continuously across major food delivery platforms — Swiggy is one of several, not a one-off build.
Support That Doesn’t Disappear After Launch
Dedicated account management, SLA-backed delivery, and proactive alerts if a schema ever needs to change.
Compliance-First, By Default
Only publicly accessible platform data is collected — no credential bypass, no restricted-API workarounds.
Custom Builds When You Need Them
Need a field, cuisine, or city we haven’t listed here? We build custom Swiggy dataset configurations on request.
Questions People Actually Ask Us About the Swiggy Dataset
These come from real conversations with restaurant brands, analysts, and engineering teams evaluating this dataset.
It’s a structured export of Swiggy’s food delivery data — menu listings, pricing, ratings, delivery-time data, and customer reviews — cleaned, deduplicated, and delivered as CSV, JSON, or an API feed.
CSV, Excel (XLS/XLSX), JSON, and API feeds by default. Parquet is available on request for Spark, Databricks, Snowflake, or BigQuery pipelines.
Pricing and ratings can refresh intraday on enterprise plans, since menu prices and delivery times change frequently. Menu listings update daily, and reviews update on a rolling basis.
Yes — tell us the cities, cuisines, fields, and refresh cadence you need, and we scope the extract accordingly rather than delivering a generic full export.
Yes, more than two years of historical menu pricing and rating data, useful for spotting genuine quality or pricing trends versus short-term fluctuations.
Yes. Because Swiggy One-linked discounts and free-delivery offers can change a restaurant’s effective menu price, the Swiggy Price Dataset flags them distinctly from standard pricing.
Yes. The Swiggy Delivery Dataset tracks average and real-time delivery-time estimates by restaurant and area, along with historical trends by time of day.
Yes. Only publicly visible pages on Swiggy’s platform are collected, using rate-limited, ethical methods. We don’t bypass logins or access restricted internal APIs.
A DIY scrape typically returns inconsistent, messy data that needs significant cleanup, especially when trying to isolate delivery-time and membership-pricing signals. This dataset is already normalized, deduplicated, and schema-stable, ready for analysis the same day it arrives.
Yes, delivery-only cloud-kitchen brands are flagged distinctly from dine-in restaurants, making it possible to benchmark them accurately against each other.
Mostly restaurant chains and franchises, cloud-kitchen operators, market research firms, AI/ML teams, restaurant consultants, and investment analysts tracking the food delivery sector.
Yes — automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever schedule you choose.
Get a Real Look at Swiggy’s Food Delivery Data
2.9M+ verified records, daily pricing and ratings refreshes, and 2+ years of historical depth across India’s leading delivery-first food platform — starting at $189.