We extract vehicle classes, location availability, base rates, taxes, and add-on pricing from Alamo. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Locations objects from alamo.com. All fields typed and schema-versioned.
"location_id": "ATL01", "branch_name": "Atlanta Hartsfield Jackson Intl Airport", "airport_code": "ATL", "city": "Atlanta", "latitude": 33.6407, "longitude": -84.4277, "phone_number": "1-844-370-9831", "operating_hours": "06:00-23:59"
| # | location_id | branch_name | address_line | city | state | postal_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Vehicle Classes objects from alamo.com. All fields typed and schema-versioned.
"sipp_code": "FCAR", "class_name": "Full Size", "example_model": "Chevrolet Malibu or similar", "passenger_capacity": 5, "door_count": 4, "luggage_capacity": 4, "transmission_type": "Automatic", "air_conditioning": true
| # | sipp_code | class_name | example_model | passenger_capacity | door_count | luggage_capacity |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Base Rates objects from alamo.com. All fields typed and schema-versioned.
"pickup_location": "ATL", "dropoff_location": "ATL", "pickup_datetime": "2026-08-15T10:00:00Z", "dropoff_datetime": "2026-08-20T10:00:00Z", "sipp_code": "FCAR", "pay_later_rate": 345.5, "currency": "USD", "mileage_policy": "Unlimited"
| # | search_id | pickup_location | dropoff_location | pickup_datetime | dropoff_datetime | sipp_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Taxes & Fees objects from alamo.com. All fields typed and schema-versioned.
"sipp_code": "FCAR", "total_price": 412.35, "base_price": 345.5, "total_taxes": 66.85, "concession_recovery_fee": 38.01, "customer_facility_charge": 15.0, "state_tax": 13.84, "one_way_drop_fee": 0.0
| # | search_id | sipp_code | total_price | base_price | total_taxes | concession_recovery_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Extras & Add-ons objects from alamo.com. All fields typed and schema-versioned.
"sipp_code": "FCAR", "collision_damage_waiver": 29.99, "extended_protection": 15.45, "gps_navigation": 12.99, "child_toddler_seat": 14.0, "toll_pass_device": 5.95, "fuel_service_option": 54.2
| # | search_id | sipp_code | collision_damage_waiver | extended_protection | personal_accident_insurance | fuel_service_option |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Alamo scraper handles complex rental reservation flows, tracking availability, dynamic pricing, and itemised taxes across thousands of locations globally.
Extract vehicle categories, SIPP codes, passenger limits, luggage capacity, and transmission types for every available vehicle.
Capture daily base rates, Pay Later vs Pay Now pricing, and total estimated costs based on specific date and time parameters.
Scrape complete branch directories including airport codes, latitude/longitude, operating hours, and shuttle instructions.
Isolate concession recovery fees, facility charges, vehicle license fees, and local taxes from the base rate.
Calculate exact drop charges by simulating distinct pickup and drop-off branch combinations.
Extract daily costs for Collision Damage Waivers, GPS units, child seats, and toll pass devices per location.
Support for US, UK, EU, and LATAM point-of-sale pricing, including currency normalisation.
Simulate young driver profiles to extract specific underage surcharges and restricted vehicle classes.
Run continuous pricing pipelines at hourly or daily intervals to monitor fleet yield management shifts.
Brief in. Clean data out.
Provide pickup locations, date ranges, and driver parameters. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for alamo.com.
Schema validation, null-rate checks, price-outlier detection, and sample rates before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Car rental pricing is highly dynamic and session-dependent. Here is how we extract accurate rates.
Alamo requires sequential API requests to establish pickup location, dates, and driver age before returning rates. Our pipeline maintains strict cookie and token state across the entire reservation funnel.
Frequent pricing queries trigger rate limits. We utilise residential ISP proxies mapped to the target point-of-sale country to ensure continuous access without IP bans.
Total prices obscure the base rate. We parse the dynamic tax breakdown payloads to separate base daily rates from airport surcharges and local taxes.
Alamo's frontend relies on JavaScript to render vehicle availability. We use Playwright to execute the required scripts and capture the final state.
Monitoring 30-day advance pricing across 50 airports requires thousands of query permutations. We distribute these requests across our cloud infrastructure to meet hourly SLAs.
Other car rental operators track Alamo's pricing shifts to adjust their own daily rates and yield management strategies.
Online travel agencies integrate direct Alamo availability and pricing data into their booking platforms.
Procurement teams audit negotiated corporate rates against public pricing to ensure contract compliance.
Analysts track vehicle class availability to infer fleet utilisation and predict market shortages.
Data science teams feed historical rate data into machine learning models to predict future price elasticity.
Market research firms aggregate rental pricing trends as an indicator of regional travel demand.
"Alamo's dynamic pricing engine responds to fleet utilisation in real time. Tracking these shifts requires continuous, session-aware extraction."
Extracting accurate car rental rates means managing complex state: pickup and drop-off coordinates, precise timestamps, and driver age parameters. DataFlirt handles the session orchestration, proxy rotation, and dynamic payload parsing so your team receives clean, structured rate tables.
Everything supported by our alamo.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright handles JavaScript rendering, session state, and interaction flows for the reservation funnel.
We maintain pools of residential ISP proxies mapped to target point-of-sale regions to ensure accurate pricing and prevent IP bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About alamo.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability data is generally permissible. DataFlirt targets only public, non-authenticated rates. We do not extract personal data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour to navigate the booking funnel.
Yes. We parse the full price breakdown to isolate base rates, concession recovery fees, facility charges, and local taxes.
Pipelines can be configured to run hourly, daily, or weekly depending on your requirements for tracking rate changes.
Yes. We can simulate searches with distinct pickup and drop-off locations to extract specific one-way drop fees.
Our packages start at defined location and date-range permutations. Contact us with your specific search matrix for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily rate monitor for 50 airports or a deep historical pricing dataset — we scope, build, and operate the pipeline. Tell us what you need.
