We extract flight schedules, dynamic pricing, fare families, seat availability, and GarudaMiles award rates from garudaindonesia.com. 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 Flight Schedules objects from garudaindonesia.com. All fields typed and schema-versioned.
"flight_number": "GA402", "origin_code": "CGK", "destination_code": "DPS", "departure_time": "2026-08-15T09:30:00+07:00", "arrival_time": "2026-08-15T12:25:00+08:00", "duration_minutes": 115, "aircraft_type": "Boeing 737-800", "stops": 0, "operating_carrier": "Garuda Indonesia"
| # | flight_number | origin_code | destination_code | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from garudaindonesia.com. All fields typed and schema-versioned.
"flight_number": "GA402", "fare_family": "Economy Flexible", "cabin_class": "Economy", "base_fare": 1850000.0, "taxes_fees": 245000.0, "total_price": 2095000.0, "currency": "IDR", "refundable": true, "price_timestamp": "2026-05-12T09:14:00Z"
| # | flight_number | fare_family | cabin_class | base_fare | taxes_fees | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seat Availability objects from garudaindonesia.com. All fields typed and schema-versioned.
"flight_number": "GA402", "departure_date": "2026-08-15", "cabin_class": "Business", "seats_remaining": 4, "waitlist_open": false, "seat_map_available": true, "pitch_inches": 42, "layout": "2-2", "scraped_at": "2026-05-12T09:14:33Z"
| # | flight_number | departure_date | cabin_class | seats_remaining | waitlist_open | seat_map_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for GarudaMiles objects from garudaindonesia.com. All fields typed and schema-versioned.
"flight_number": "GA402", "route": "CGK-DPS", "cabin_class": "Economy", "award_type": "Saver", "miles_required": 12500, "taxes_fees": 150000.0, "currency": "IDR", "award_availability": true
| # | flight_number | route | cabin_class | award_type | miles_required | taxes_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Network objects from garudaindonesia.com. All fields typed and schema-versioned.
"origin_code": "CGK", "origin_city": "Jakarta", "destination_code": "AMS", "destination_city": "Amsterdam", "frequency_per_week": 6, "direct_flight": true, "distance_miles": 7045, "active_status": true
| # | origin_code | origin_city | destination_code | destination_city | frequency_per_week | direct_flight |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our airline scraper handles every layer of the booking engine: flight schedules, dynamic pricing, fare families, and GarudaMiles award availability — with session management and anti-bot circumvention built in.
Flight numbers, departure/arrival times, durations, layovers, and aircraft types scraped across the entire Garuda Indonesia network.
Extract base fares, taxes, and total prices across all cabin classes (Economy, Business, First) and fare families (Promo, Affordable, Flexible).
Monitor remaining seats per fare bucket and cabin class to gauge demand and flight load factors.
Track miles required, applicable taxes, and award seat availability for frequent flyer redemption analysis.
Capture checked baggage allowances, excess baggage fees, and seat selection costs associated with specific fare types.
Extract pricing in IDR, USD, EUR, or AUD by simulating different geographical points of sale.
Distinguish between Garuda Indonesia operated flights and codeshare partners (e.g., SkyTeam alliance members).
Monitor critical routes with high-frequency polling to detect intra-day price adjustments and yield management changes.
Run continuous pipelines and only receive records when prices, schedules, or seat counts change.
Brief in. Clean data out.
Provide O&D (Origin & Destination) pairs, date ranges, and cabin classes. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for garudaindonesia.com.
Schema validation, null-rate checks, price-outlier detection, and sample schedules before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airline booking engines invest heavily in scraping detection to protect their pricing data. Here is how we stay resilient.
Airline booking engines drop connections if they detect automated IP ranges. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management to bypass rate limits.
Garuda Indonesia's pricing is heavily JavaScript-rendered and requires sequential API calls mimicking a user search. We run full Playwright browser sessions to navigate the search flow and extract the final pricing matrix.
Airlines frequently update their booking engine UI. Our selector strategy uses multiple fallback chains per field — CSS selectors, XPath, and API payload interception — so a layout change does not break your data pipeline.
For large route networks, we maintain a hash index of last-seen values per flight. Subsequent runs only push diffs — reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, and coverage drops — and respond before you notice.
Rival airlines and OTAs monitor Garuda Indonesia's pricing, fare families, and promotional discounts to adjust their own yield management algorithms.
Online Travel Agencies aggregate schedule and pricing data to offer comprehensive flight search without relying entirely on expensive GDS queries.
Frequent flyer platforms scrape GarudaMiles redemption rates and award availability to alert users when premium cabin seats open up.
Aviation analysts track frequency changes, seasonal route deployments, and aircraft type assignments to understand capacity planning.
Corporate travel managers audit publicly available fares against their negotiated corporate rates to ensure contract compliance.
Financial analysts correlate seat availability trends and fare bucket closures with macroeconomic indicators to forecast airline revenue.
"Garuda Indonesia's route network and pricing engine emit millions of data points daily — but none of it is queryable unless you build the pipeline."
Most teams underestimate the investment required: reliable airline scraping requires residential proxies, session state management, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our garudaindonesia.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across ID and SG regions. Rotation happens per-session to maintain consistent search context. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 garudaindonesia.com scraping, legality, and pipeline operations.
Ask us directly →We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline. We monitor for rate spikes in real time and trigger pool rotation automatically.
Yes. We can scrape the miles required, associated taxes, and seat availability for GarudaMiles redemption across different cabin classes and routes.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on a defined route set. Full network refreshes at daily cadence complete within a 4-8 hour window depending on size.
Yes. We can configure the pipeline to extract fares in IDR, USD, EUR, AUD, or other supported currencies by simulating the appropriate point of sale and locale.
Our smallest packages start at a defined route list (typically 100-500 O&D pairs) with daily delivery. For larger networks or custom schema requirements, we price based on volume and delivery frequency.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per flight for remaining seats, base fare, and total price from the date your pipeline starts.
Absolutely. We provide a sample run of up to 20 routes as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off schedule dump or a continuous price-monitoring feed across 10,000 routes — we scope, build, and operate the pipeline. Tell us what you need.
