Stop Searching. Stop Waiting. Start Streaming.
The hardest part of EO isn't analysis - it's moving the data. Terrafloww gives you instant access to global catalogues and streams pixels directly to your model.
Powered by Rasteret
The fastest satellite image processing library. Read satellite images 11x faster than traditional tools.
Performance Comparison
A Global Archive at Your Fingertips
Instant access to global satellite imagery
Sentinel-2 Level-2A Surface Reflectance
Copernicus Sentinel-2 L2A
Copernicus Sentinel-2 Level-2A provides atmospherically corrected surface reflectance imagery across 13 spectral bands. The dataset covers all land surfaces between 84°N and 56°S, with a 5-day revisit time at the equator. Level-2A processing includes Scene Classification (SCL), Aerosol Optical Thickness (AOT), and Water Vapor (WVP) products.
USGS Landsat Collection 2 Level-2 Surface Reflectance
USGS Landsat Collection 2
Landsat Collection 2 Level-2 Surface Reflectance provides the longest continuous space-based record of Earth's land, spanning from 1982 to present across Landsat missions 4, 5, 7, 8, and 9. Surface reflectance data is atmospherically corrected and includes quality assessment bands for clouds, shadows, snow, and saturation.
Impact Observatory 10m Annual Land Use/Land Cover
Impact Observatory LULC
Global 10-meter annual land use/land cover classification derived from Sentinel-2 imagery using deep learning models. Provides 9-class classification globally. Generated by applying deep learning models trained on human-labeled pixels from National Geographic Society. Average accuracy over 75%.
Digital Earth Africa CHIRPS Daily Rainfall
CHIRPS v2.0
Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) daily rainfall dataset. Quasi-global coverage (50°S-50°N) at 0.05 degree resolution, spanning from 1981 to near-present. CHIRPS combines satellite imagery with in-situ station data to create gridded rainfall time series for drought monitoring and trend analysis.
Your Infrastructure is Obsolete.
Why build a 15-step pipeline for a simple NDVI? Terrafloww collapses the stack. From `import` to `insight` in 3 lines of Python.
import rasteret
# Fetch Sentinel-2 data
ds = rasteret.get_xarray(
geometries=[bbox],
bands=["red", "nir", "visual"],
date_range=("2025-01-01", "2025-01-31"),
dataset="terrafloww/sentinel2_l2a_earthsearch",
cloud_cover_lt=20,
)
# Calculate NDVI instantly
ds["ndvi"] = (ds["nir"] - ds["red"]) / (ds["nir"] + ds["red"])
>>> Processing complete: 847ms ✓No Downloads
Stream data directly from cloud storage
No Memory Errors
Process petabytes without RAM limits
No Boilerplate
Focus on analysis, not infrastructure
The Pixel Economy: Stop Paying for Empty GeoTIFFs
Traditional satellite data pricing makes you pay for entire scenes. We only charge for the pixels you actually process.
Traditional Model
Full scene buy-in
Terrafloww Model
Pay-as-you-stream
| Feature | Traditional | Terrafloww |
|---|---|---|
| Pricing Model | Per Scene / Full File | Per Pixel Processed |
| Minimum Purchase | $100+ per scene | Pay what you use |
| Data Transfer | Download entire file | Stream only needed pixels |
| Storage Costs | Your responsibility | Included |
| Processing Time | Hours to days | Milliseconds |
| Memory Limits | Your hardware limits | Unlimited streaming |
Simple, Transparent Pricing
Start experimenting for free. Scale when you're ready.
Free
Perfect for testing and small experiments.
- 10 Credits / month included
- Max 5 users / org
- Access to Marketplace
- Community Support
Pro
For power users and data publishers.
- 100 Credits / month included
- Unlimited users
- Create & Publish 1 Dataset
- Priority Support
- Commercial Usage
- Usage & Geo-Analytics Dashboard for Org Admins
Add-ons & Credits
Buy More Credits
Run out of monthly credits? Top up anytime.
Additional Datasets (Pro only)
Need to publish more? Add capacity as needed.
*Requires active Pro subscription
Cloud-Native Architecture
Built on open standards. Designed for scale. Ready for production.
Discover
Search our catalog of global satellite imagery from major providers
Stream using Rasteret
Zero-copy data streaming directly to your compute environment
Analyze
Simple Python SDK that feels like local data - but planetary scale