Mapbox vs MapLibre vs Custom GeoAI: Which Should You Use?
Three very different choices hide behind 'we need a map'. A managed platform, an open-source renderer you host yourself, or a custom geospatial system with AI on top. Here is how we decide, after building all three.
By the TARDIS Solutions engineering team · Updated
What each option actually is
| Mapbox | MapLibre | Custom GeoAI stack | |
|---|---|---|---|
| What you get | Managed maps, tiles, search, navigation SDKs | Open-source map renderers (web and native) | Your own data pipeline, tiles, search and AI layer |
| Licence | Commercial; usage-based pricing | Open source (BSD-style licence) | Yours; built from open components |
| Basemap data | Included | Bring your own or use a provider | Bring your own (often OpenStreetMap) |
| Cost at scale | Grows with map loads and API calls | Hosting and bandwidth only | Build cost up front, low running cost |
| Offline / air-gapped | Limited | Yes, with self-hosted tiles | Yes, by design |
| Data stays in your network | No | Yes | Yes |
Choose Mapbox when
- You need good-looking maps, geocoding and navigation quickly and your traffic is modest.
- Your team doesn't want to operate tile infrastructure.
- Sending location queries to a third-party API is acceptable for your users and regulators.
Mapbox's newer SDKs are proprietary and billed by usage, which is fine at small scale. The thing to model before you commit is your bill at ten times today's traffic.
Choose MapLibre when
MapLibre began as a community fork of Mapbox GL JS when Mapbox changed the licence of its v2 release, and has since grown into an independent project with web and native renderers. It renders the same style of vector maps, but you choose where the tiles come from. With formats like PMTiles you can serve an entire region's basemap as static files from object storage, which is cheap and works offline.
- Usage-based pricing would become your largest infrastructure cost.
- You need offline maps for field teams or an air-gapped deployment.
- Data residency rules mean location data must stay in your network.
- You want full control of the style and the data in the basemap.
Choose a custom GeoAI stack when
When the map isn't the product; the answers are. If users need to ask 'which of our 40,000 sites are within 2 km of a flood zone and had a complaint this month', a renderer won't help. You need spatial data modelled properly (usually PostGIS), search that combines full text with geometry, and increasingly an AI layer that turns a question into a correct spatial query and explains the result.
- Your users ask questions of spatial data, not just look at it.
- You merge several sources (government records, your own assets, satellite imagery) and need them reconciled.
- You need compliance-grade outputs, for example EUDR deforestation evidence.
- Latency and cost at very high request volumes matter.
Our founder led the geospatial platform at Ola Krutrim, which served around 2 billion API requests a day at sub-50ms p99 with an in-house geocoder and a vector tile pipeline. That is the extreme end of custom; most teams need a fraction of it, but the same principles apply.
Where AI on maps helps, and where it doesn't
- Helps: turning natural-language questions into spatial queries, summarising what a map shows, classifying satellite imagery, cleaning messy addresses.
- Doesn't help: anything where the model can invent a location or a boundary. Generated geometry must always be checked against real data before anyone acts on it.
A common path: start on MapLibre with self-hosted tiles, put your data in PostGIS, and add search and AI only where users actually ask questions. You can move from Mapbox to MapLibre later, but it's cheaper to start there if scale is likely.
Frequently asked questions
Is MapLibre a drop-in replacement for Mapbox?
For rendering, largely yes: it uses the same style specification lineage, and moving from Mapbox GL JS v1 is straightforward. Mapbox-specific services (their geocoding, directions, hosted tiles) need replacements, which is where most of the migration work is.
Where do we get basemap data for India?
OpenStreetMap is the usual base, enriched with government and your own data. Address quality varies a lot across India, which is why we built an offline geocoder covering the 22 scheduled languages.
Can maps work fully offline?
Yes. With MapLibre and tiles packaged as files (for example PMTiles), plus a local geocoder, maps and search work with no connectivity. We have shipped this for field teams and for an air-gapped deployment.