Platform · Kayak

Kayak Data Scraping

Kayak does not sell the ticket. Every fare on the page is another seller's offer, shown for one query, at one moment.

Kayak data scraping covers flight and travel results from a metasearch engine. Two things shape it. A fare shown here is a referred offer from an airline or agency, so the seller is part of the record. And results depend on the query — route, dates, passengers, cabin and where it was searched from. Separately, airfare collection sits behind a terms position that is still open, and this page does not get ahead of it.

Our flight fare page explains why most requests here are for history nobody can sell. This page is about what a metasearch fare is, for the part that can be collected.

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kayak_schema_sample.jsonl LIVE FEED

{"query_id":"q-LHR-JFK-2026-11-12-1A-Y-GB", "origin":"LHR","destination":"JFK","market_searched_from":"GB", "seller_name":"example agency","fare_is_referred":true, "price_displayed":,"fee_basis_displayed":"bags_excluded"} {"terms_position_status":"open","collecting":false, "history_backfill":"not_obtainable"}

schema sample · no collection until the terms position is settleda referred offer carries its seller and its query · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Kayak or its owners. Kayak and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Kayak at a glance

How we handle Kayak specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Kayak — metasearch, part of Booking Holdings
A fare here is: A referred offer from an airline or agency
So: seller on every fare
Results depend on: The full query, and where it was run from
Sibling: Momondo — same owner and operator
History: Not retrospective. A forward panel starts at commissioning
Status: Terms position open — see flight fare page
What we do now: Scope the query set and assess; no collection yet

Platform specifics

Referred offers, and the query behind them

These are the reasons a Kayak dataset needs its own handling rather than a shared retail schema.

A metasearch fare belongs to someone else

Kayak shows fares from airlines and agencies and sends you to them to book. So a price on the results page is the seller's offer as Kayak displayed it.

The seller is part of the fare — the same flight can appear from several sellers at different prices.
The displayed price can differ from what the seller's own site shows a moment later.
Fees and bags are presented according to the search settings, not always included.
Sort order is the platform's choice, and we do not model it.

So seller_name, fare_is_referred and fee_basis_displayed travel with every fare — the same position our Trivago page takes for hotels.

The query is part of the record

Route, dates, passengers, cabin, currency and the market searched from all change the result. query_id carries all of them. A fare without its query cannot be reproduced.

The open position, and what we do in the meantime

Where this stands

Displayed fares are collectable subject to a terms position that is still open — our flight fare page sets it out. We scope and assess now; collection starts when that position is settled for your use.

History is not for sale

Past fares on a route exist only where someone was recording at the time. No vendor can sell you a retrospective series, including us. The buildable option is a forward panel: fixed routes, fixed advance-purchase windows, sampled on a schedule from the day it starts.

Kayak and Momondo

Both are run by the same company. If both are wanted, overlap is measured first — see our Momondo page.

What we do not do

Promise live collection before the terms position is settled, sell history, or model the platform's sort order.

Scope

What we collect on Kayak, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

The query set scoped now: routes, dates, cabins, markets
Which of the three kinds of fare data you need, named before quoting
seller_name and fare_is_referred on every fare, once collecting
query_id carrying route, dates, passengers, cabin and market
fee_basis_displayed, since bags and fees vary by search setting
A forward panel design from commissioning
Overlap with Momondo measured if both are wanted
Currency and market searched from on every fare
Stay honest about what is still open

❌ What we do not, and why

Live collection promised before the terms position is settled
Historical fares sold or backfilled
A fare without its query
A referred price presented as Kayak's own price
Passenger, account or booking data

Core Kayak fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
query_id / origin / destination / depart_date / return_date	The query. Without it nothing reproduces
passengers / cabin / market_searched_from	The rest of the query
seller_name / fare_is_referred	Whose offer this is
price_displayed / currency	As shown
fee_basis_displayed	What the price includes, per search setting
carrier / stops / duration	The itinerary
position	As displayed. Not modelled
observed_at / lead_time_days	When, and how far ahead
panel_schedule_id	For a forward panel
terms_position_status	Open until settled
result_count	How many offers the query returned

Use cases

What teams do with Kayak data

Forward fare panel design

Fixed routes and advance-purchase windows sampled on a schedule, which is the only way to build fare history — from the day it starts.

Seller mix on a route

Which airlines and agencies appear for a query, and at what prices, once collection is cleared.

Query-reproducible observations

Every fare carries its full query, so a result can be interpreted and repeated.

Scoping before the position settles

Routes, windows and markets agreed now, so collection can start as soon as the terms position allows.

The 24-hour sample — run on your sources, not ours

Send us a Kayak item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Kayak is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Kayak data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what travel & hospitality data covers, and a Kayak-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Kayak data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Not yet. Displayed fares are collectable subject to a terms position that is still open, as our flight fare page sets out. We scope and assess now; collection starts when that position is settled for your use.

No, and nobody can. Past fares exist only where someone was recording at the time. The option is a forward panel, which builds history from the day it starts.

No. It is an airline's or agency's offer that Kayak displays and refers you to. The seller is part of every fare we record.

Because route, dates, passengers, cabin, currency and the market searched from all change the result. A fare without its query cannot be reproduced.

Both are run by the same company, so measure the overlap first. Collecting the difference is usually the better buy.

We quote once the terms position is settled, on routes, date windows, markets and frequency. Scoping and the assessment are free now.

Talk to us about which of the three kinds of fare data you actually need.

See real Kayak data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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