Mapbox Turf
Location intelligence software
Business intelligence software
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- Ease of use
- Ease of management
- Quality of support
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What is Mapbox Turf
Mapbox Turf (commonly referred to as Turf.js) is a geospatial analysis library used to perform spatial operations such as buffering, intersections, distance calculations, and aggregations on GeoJSON data. It is primarily used by developers and data teams to add location analytics to web and mobile mapping applications or to preprocess geospatial datasets. The product is delivered as a JavaScript module ecosystem rather than an end-user analytics application, and it typically runs in browser or Node.js environments.
Broad geospatial function library
It provides a large set of reusable geospatial functions (e.g., buffer, union, intersect, point-in-polygon, distance, along, bbox) that cover many common location-intelligence workflows. This reduces the need to implement spatial math from scratch in application code. The GeoJSON-first design makes it straightforward to chain operations in data pipelines and mapping apps.
Developer-friendly integration model
It integrates as a JavaScript dependency and can run client-side or server-side, which fits modern web application architectures. Teams can embed spatial analysis directly into custom products rather than relying on a separate GUI tool. This approach supports fine-grained control over how analysis is executed and how results are rendered on maps.
Works across mapping stacks
Because it operates on standard GeoJSON inputs/outputs, it can be used with multiple mapping and visualization frameworks rather than requiring a specific end-user platform. This helps teams keep geospatial logic portable across projects. It also supports use cases where analysis is needed without standing up a dedicated geospatial database.
Not an end-user BI tool
It does not provide dashboards, report builders, semantic layers, or governed self-service analytics typically expected in business intelligence software. Organizations looking for non-technical workflows must build their own UI and data management around the library. As a result, adoption usually requires engineering resources.
Performance limits at scale
Running complex spatial operations on large datasets in JavaScript can be resource-intensive, especially in browsers with memory and CPU constraints. For high-volume batch processing, routing-scale workloads, or heavy polygon operations, teams may need server-side processing, tiling, or a spatial database. This adds architectural complexity compared with managed location-intelligence platforms.
Requires geospatial data hygiene
Outputs depend on input geometry quality, coordinate reference assumptions, and correct GeoJSON structure. Handling edge cases (invalid polygons, antimeridian issues, precision/units) often requires additional validation and testing. This can increase implementation time compared with tools that include built-in data cleansing and QA workflows.
Plan & Pricing
Pricing model: Open-source / Free
Pricing details: Turf (Turf.js) is an open-source geospatial analysis library. Mapbox documentation states that Turf is an open-source JavaScript library and explicitly notes "Turf is not a Mapbox product." Mapbox provides documentation and SDK ports (Java, Swift) for Turf operations that run client-side or on-device. Mapbox’s pricing page does not list any paid plans, SKUs, or usage charges for Turf.
Notes & usage: Turf functions are typically executed locally (in-browser or on-device) and do not require Mapbox API calls; any Mapbox SDK ports similarly run without Mapbox billing for those operations.
Seller details
Turf.js (open-source project; commonly distributed and maintained within the Mapbox ecosystem)
Open Source
https://turfjs.org/
