Google Earth Engine
Location intelligence software
Business intelligence software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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Large
- Agriculture, fishing, and forestry
- Public sector and nonprofit organizations
- Energy and utilities
What is Google Earth Engine
Google Earth Engine is a cloud-based geospatial analysis platform for processing and analyzing large-scale satellite imagery and other Earth observation datasets. It is used by GIS analysts, data scientists, researchers, and public-sector teams for land cover change detection, environmental monitoring, disaster assessment, and spatial modeling. The platform combines a managed data catalog with server-side computation and APIs for scripting and integration, rather than focusing on sales territory mapping or indoor location use cases.
Large geospatial data catalog
It provides access to a broad catalog of satellite imagery and geospatial datasets that can be analyzed without users managing raw data storage and tiling workflows. This reduces time spent on data acquisition and preprocessing for common Earth observation tasks. The catalog-centric approach is a differentiator versus tools that primarily focus on business address data, routing, or field sales mapping.
Scalable cloud processing model
It runs geospatial computations server-side, which supports analysis over very large areas and long time ranges that are difficult to process on a desktop GIS. Users can execute batch-style analyses and generate derived raster/vector outputs without provisioning their own compute clusters. This is well-suited to remote sensing and environmental analytics workloads compared with location tools optimized for operational mapping and CRM workflows.
Developer-friendly APIs and scripting
It supports programmatic workflows through JavaScript and Python APIs, enabling reproducible analyses and integration into data science pipelines. Teams can automate processing, parameter sweeps, and model runs rather than relying only on point-and-click interfaces. This makes it practical for organizations that need custom geospatial analytics beyond standard dashboards.
Not a general BI platform
It does not function as a full business intelligence suite for enterprise reporting, semantic models, or broad non-spatial analytics. Organizations typically need separate BI tools for KPI dashboards, governed metrics, and business data modeling. As a result, it fits best as a geospatial analytics engine feeding downstream reporting rather than replacing BI software.
Steep learning curve for GIS
Effective use often requires familiarity with geospatial concepts (projections, raster processing, time-series imagery) and scripting. Users expecting a simple operational mapping experience may find it less approachable than tools designed for sales mapping or location-based workflow management. Training and prototyping time can be significant for non-technical teams.
Constraints on data governance
Data residency, access controls, and compliance requirements may be harder to satisfy for some regulated organizations depending on how datasets and outputs are managed in the cloud environment. Integrating proprietary datasets can require additional setup and careful permissioning. Some use cases may require exporting results to other systems for governance, auditing, or long-term retention.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Limited (self-serve) | Usage fees only (no monthly platform fee) | Billed based on usage fees only; no usage credits, no performance add‑ons, and no SLAs. Intended for intermittent, non-business-critical, non high-capacity workloads (self-select via the Code Editor). |
| Basic | $500 per month | Includes 100 Batch EECU-hour/month credit, 33 Online EECU-hour/month credit, 100 GB Earth Engine Cloud storage credit. SLA not available for this tier (basic is intended for small teams/small workloads). |
| Professional | $2,000 per month | Includes 500 Batch EECU-hour/month credit, 166 Online EECU-hour/month credit, 1 TB Earth Engine Cloud storage credit. SLA included; VPC Service Controls supported; higher concurrency limits (up to 500 high-volume API requests per project on request). |
| Premium | Contact sales | Custom allocations and SLAs; contact Google Sales for pricing and enterprise configuration. |
Additional usage pricing (on-demand):
- Compute (Online and Batch): $0.40 per EECU-hour (US-Central-1). Tiered discounts apply based on monthly EECU consumption: $0.40 (0–10,000), $0.28 (10,000–500,000), $0.16 (>=500,000).
- Storage: $0.026 per GB‑month (US-Central-1).
- Data extraction: currently no charge but will be priced based on standard Google Cloud data transfer fees starting later in 2024.
Notes: Platform (monthly) fees provide EECU and storage credits that refill monthly and are prorated for partial months; once credits are depleted, standard usage fees apply.
Seller details
Google LLC
Mountain View, CA, USA
1998
Subsidiary
https://cloud.google.com/deep-learning-vm
https://x.com/googlecloud
https://www.linkedin.com/company/google/
