> For the complete documentation index, see [llms.txt](https://resources.atriptech.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://resources.atriptech.com/api-document/product-guides/extensions-and-integrations/atlas-data-feed.md).

# Atlas Data Feed

Build a local flight-shopping layer with Atlas pricing data, then confirm and ticket through Atlas Transaction APIs.

Atlas Data Feed delivers flight pricing data to your local platform.

Use it for high-volume shopping. Use Atlas Transaction APIs to confirm price and availability, create orders, and issue tickets.

{% hint style="info" %}
Data Feed supports search and display. It is not the final booking source of truth.
{% endhint %}

### Why use Data Feed

Separate high-volume shopping from transactional booking.

Your platform queries local data for search, comparison, ranking, and recommendations. Atlas handles the real-time transaction when a traveller is ready to buy.

* Reduce dependency on real-time `search.do` calls during display.
* Build local search, ranking, and commercial rules around structured fare data.
* Keep final price, availability, payment, and ticketing in Atlas.

### How it works

```mermaid
flowchart LR
    A[Atlas Data Feed] --> B[Your database or cache]
    B --> C[Search, compare, rank, recommend]
    C --> D[Traveller selects itinerary]
    D --> E[getOffers.do]
    E --> F[order.do]
    F --> G[pay.do]
    G --> H[Query order or Webhook]
```

1. Atlas delivers full and incremental price files to your SFTP server.
2. Your platform loads the data into a local database, cache, or search index.
3. Travellers search and select an itinerary using your local shopping layer.
4. Call `getOffers.do` to retrieve the latest bookable price and `OfferId`.
5. Create the order, pay, and follow the final ticketing status.

{% hint style="warning" %}
Do not use pushed data as the final bookable price. Always call `getOffers.do` before `order.do`.
{% endhint %}

### Use cases

#### High-volume shopping and comparison

Use local data for frequent searches, filters, comparisons, and ranking.

This suits OTAs, metasearch platforms, and corporate travel tools. Your shopping experience remains responsive during peak traffic.

#### Your own shopping or third-party data source

Keep your existing search engine, recommendation service, or external shopping source.

When a traveller selects a known itinerary, use `getOffers.do` for an Atlas bookable offer. Continue with `order.do` and `pay.do` for fulfilment.

#### Dynamic packaging and commercial rules

Combine flight data with hotels, insurance, loyalty benefits, or margin rules.

Run batch pricing and ranking locally. Confirm the final flight price and availability through Atlas when the traveller checks out.

#### AI search and recommendations

Index structured itinerary, fare, baggage, availability, and price data in your own retrieval system.

Use it to power natural-language search, recommendations, and assisted selling. Confirm every selected itinerary in real time before booking.

#### Analytics and operations

Use the full and incremental files for pricing analysis, route coverage reviews, supply monitoring, and reporting.

This avoids repeated transactional API calls for analysis workloads.

### Choose the right booking path

| Your model                                              | Recommended path                                   |
| ------------------------------------------------------- | -------------------------------------------------- |
| Atlas is your shopping and booking layer                | `search.do` → `verify.do` → `order.do` → `pay.do`  |
| You operate the shopping layer and want Atlas ticketing | Data Feed → `getOffers.do` → `order.do` → `pay.do` |

Data Feed works best when you need local shopping capability. It does not require replacing your existing booking APIs.

### What changes for existing Atlas customers

Existing `search.do` and `verify.do` integrations continue to work.

To adopt Data Feed, move shopping traffic to your local data layer. Replace the final `search.do` and `verify.do` steps with `getOffers.do` after itinerary selection.

You need to:

1. Receive full and incremental files through SFTP.
2. Upsert records by `atlas_flight_fare_id` and `update_time`.
3. Build or reuse local storage and a query layer.
4. Call `getOffers.do` only when a traveller is ready to continue.

`getOffers.do` and `verify.do` share a default `60 QPM` fulfilment pool. Do not use `getOffers.do` for high-volume display queries.

### Is Data Feed right for you?

Choose Data Feed when you need high-throughput local shopping, custom ranking, batch processing, or AI retrieval.

Keep the standard search path when Atlas should remain your primary shopping layer. Data Feed is not suitable when pushed prices must be treated as final booking prices.

### Next steps

{% content-ref url="/spaces/UcaRG2qIaBgtVwgrBEGX/pages/u2FijdronIMEksIXebxV" %}
[Atlas Data Feed — Technical Integration Guide](/api-document/product-guides/extensions-and-integrations/atlas-data-feed/flight-data-feed.md)
{% endcontent-ref %}

{% content-ref url="/spaces/UcaRG2qIaBgtVwgrBEGX/pages/NS7gkZIr0mFD8f0vV1sj" %}
[Get Offer](/api-document/product-guides/booking/booking-flows/get-offer-flow.md)
{% endcontent-ref %}