We extract vehicle telemetry, fleet density, pricing tiers, and charge levels across all Share-Now operating cities. Delivered as clean JSON, CSV, or Parquet to your warehouse.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Vehicle Telemetry objects from share-now.com. All fields typed and schema-versioned.
"vehicle_id": "SN-BER-8492", "make": "BMW", "model": "i3", "latitude": 52.520008, "longitude": 13.404954, "battery_level_pct": 84, "range_km": 210, "status": "AVAILABLE"
| # | vehicle_id | model | make | license_plate | latitude | longitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Rates objects from share-now.com. All fields typed and schema-versioned.
"vehicle_id": "SN-BER-8492", "city": "Berlin", "price_per_min": 0.33, "currency": "EUR", "hourly_rate": 14.99, "daily_rate": 49.99, "drop_off_fee": 0.0
| # | vehicle_id | city | price_per_min | currency | hourly_rate | daily_rate |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fleet Metadata objects from share-now.com. All fields typed and schema-versioned.
"vehicle_id": "SN-BER-8492", "seats": 4, "transmission": "AUTOMATIC", "doors": 5, "colour": "White", "engine_type": "ELECTRIC", "clean_status": "GOOD"
| # | vehicle_id | seats | transmission | doors | colour | engine_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Zones & Geofences objects from share-now.com. All fields typed and schema-versioned.
"zone_id": "Z-BER-MITTE", "city": "Berlin", "is_parking_allowed": true, "is_dropoff_allowed": true, "parking_fee": 0.0, "active_vehicles": 142
| # | zone_id | city | polygon_coordinates | is_parking_allowed | is_dropoff_allowed | parking_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for City Availability objects from share-now.com. All fields typed and schema-versioned.
"city_name": "Berlin", "country": "Germany", "total_vehicles": 1205, "available_vehicles": 984, "reserved_vehicles": 142, "last_updated": "2026-05-12T09:14:00Z"
| # | city_name | country | total_vehicles | available_vehicles | reserved_vehicles | maintenance_vehicles |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Share-Now pipeline handles the complexities of spatial API polling, token rotation, and coordinate boundary mapping. You receive clean, structured fleet data ready for analysis.
Capture exact latitude and longitude coordinates for every available vehicle across all active cities.
Track charge percentages, fuel levels, and estimated range in kilometres for individual vehicles.
Extract per-minute rates, hourly packages, daily caps, and zone-based drop-off surcharges.
Export operational boundaries, parking zones, and restricted areas as structured GeoJSON polygons.
Extract make, model, transmission type, seating capacity, and engine type for the entire fleet.
Automated session management and token generation to maintain uninterrupted access to Share-Now endpoints.
Calculate vehicle concentration per square kilometre to identify high-demand zones and supply gaps.
Execute grid-based spatial queries at sub-minute intervals to capture rapid vehicle turnover.
Monitor Berlin, Paris, Milan, Madrid, and all other Share-Now operating regions from a single pipeline.
Brief in. Clean data out.
Provide target cities, polling frequency, and required fields. We configure the spatial bounding boxes.
We deploy grid-based API crawlers, proxy rotation, and token management systems for the target regions.
Coordinate validation, deduplication checks, and null-rate monitoring before full production launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Mobility apps rely on dynamic map viewports and strict rate limits. Here is how we maintain continuous extraction.
Share-Now APIs only return vehicles within a specific bounding box. We divide cities into overlapping coordinate grids and poll them concurrently to ensure complete fleet coverage without missing edge-case vehicles.
High-frequency polling triggers IP bans. We distribute requests across thousands of European residential proxies, ensuring no single IP exceeds the API rate limit threshold.
Overlapping bounding boxes cause duplicate vehicle records. Our pipeline maintains a real-time Redis state to deduplicate vehicles based on unique IDs and timestamps before delivery.
Mobile APIs require valid session tokens and cryptographic signatures. We reverse-engineer the authentication flow to generate fresh, valid headers for every polling cycle.
Mobility apps frequently update their API response structures. We monitor payload schemas in real time, alerting our engineers to structural changes before they corrupt your downstream data.
Rival mobility operators track Share-Now fleet sizes, pricing changes, and expansion zones to inform their own market strategies.
City councils and transit authorities analyse car-sharing density to optimise public transport routes and parking infrastructure.
Pricing analysts correlate vehicle availability with time of day and weather patterns to build predictive surge-pricing algorithms.
Charging network operators track battery depletion rates and parking locations to determine optimal sites for new charging stations.
Investors and analysts monitor vehicle utilisation rates across different cities to evaluate operational efficiency and growth potential.
Data scientists model vehicle movement patterns to understand demand hotspots and optimise manual vehicle relocation strategies.
"Share-Now operates one of the most dynamic mobility fleets in Europe. Tracking vehicle movement and pricing requires continuous spatial polling, not static scraping."
Extracting mobility data at scale demands precise grid-based API polling, token rotation, and spatial deduplication. DataFlirt manages the underlying infrastructure, rate limits, and proxy rotation so your analysts receive clean, structured telemetry without maintaining complex geospatial crawlers.
Everything supported by our share-now.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.
We utilise PostGIS and custom Python geospatial libraries to generate overlapping bounding boxes, ensuring complete city coverage without missing vehicles on grid edges.
Redis clusters maintain active vehicle states across polling cycles. Vehicles detected in multiple overlapping grids are merged into a single accurate record before delivery.
Our infrastructure automatically reverse-engineers and rotates authentication tokens, preventing session timeouts and bypassing strict endpoint rate limits.
Data delivered to where your team already works — no new tooling required.
About share-now.com scraping, legality, and pipeline operations.
Ask us directly →We can configure pipelines to poll specific city grids at sub-minute intervals. The exact frequency depends on the size of the target area and your specific data freshness requirements.
We primarily target the undocumented mobile and web APIs used by the Share-Now frontend. This provides cleaner, more structured data and allows for precise spatial querying.
No. Once a vehicle is rented, it disappears from the public availability map. We can track the exact location it was rented from and the location it was returned to, but not the interim route.
Our pipelines use Redis to maintain a real-time state of all detected vehicles. If a vehicle appears in two adjacent polling grids, our deduplication engine merges the records based on the vehicle ID and timestamp.
We begin accumulating historical data from the moment your pipeline is commissioned. We do not maintain a pre-existing historical database of Share-Now vehicle movements.
We actively monitor API endpoint changes and schema modifications resulting from the Share-Now and Free2move integration. Our pipelines are updated to maintain extraction continuity across both platforms.
20-minute scoping call. Pilot dataset within the week. Production within two. Specify your target cities and polling frequency. We handle the proxies, grid mapping, and API extraction. Contact us for a technical scoping call.
