Overture Maps: Open Geospatial Data for GIS, Mapping, and Location Analysis
Overture Maps is an open geospatial data project that publishes normalized, theme-based map data for addresses, buildings, places, transportation, divisions, and base features. Its datasets are designed for map production, search, routing, geographic analysis, and location-data applications. Overture distributes cloud-native GeoParquet files through Amazon S3 and Microsoft Azure, with access through its Python tools, DuckDB, GIS software, partner mirrors, and an interactive explorer. Coverage and licensing vary by theme and upstream source, so Overture should be treated as a structured, evolving location-data ecosystem rather than one uniformly authoritative global database.
Overture Maps is an important layer in the open geospatial ecosystem because it focuses on making large, heterogeneous map sources easier to consume together. Instead of publishing one undifferentiated world file, Overture organizes data into themes and feature types with a shared schema, stable identifiers in many themes, cloud-friendly partitions, and recurring releases. That makes it useful for people building maps, search systems, routing networks, spatial indexes, geographic analyses, and applications that need to connect physical features to one another.
How EDK fits
For: GIS analysts, cartographers, geospatial developers, data engineers, researchers, mapping teams, routing specialists, and organizations evaluating open location-data sources.
Overture Maps relates directly to the problem of finding and understanding the physical world because its themes describe tangible geographic entities: addresses, buildings, places, roads and other transportation features, administrative divisions, land, water, infrastructure, and related base features. Its value is strongest as a structured external dataset that can be queried, filtered, joined, and combined with other geographic sources. In an E2-oriented workflow, Overture could serve as one important source layer for identifying candidate buildings, roads, destinations, addresses, administrative areas, and physical infrastructure. E2's world-model perspective is broader than any single Overture release: the useful connection is the ability to place Overture features alongside other location data, compare them over geography, measure proximity, aggregate features by region, and use them as inputs to computation about the planet. This page does not imply that Overture provides E2's search, world-model, or computation capabilities; it explains where an external open dataset can contribute to those kinds of geographic questions.
- •Use Overture buildings, addresses, places, and transportation features as an external geographic layer when identifying physical entities in a city, region, or corridor, then join or compare them with other environmental, infrastructure, public-service, or imagery data in a broader world-model workflow.
- •Use Overture's theme and type partitions, bounding boxes, and GeoParquet representation to support geographic computation such as counting places within administrative areas, measuring building density near roads, ranking destinations by proximity, or comparing feature coverage across regions. Results should preserve the Overture release, source attribution, and known quality limitations.
- •Use Overture transportation and place features as reference inputs for spatial indexing, route-network preparation, accessibility studies, or location search, while validating the data against authoritative local sources when operational or regulatory accuracy matters.
Dataset profile
Formats
Cloud-native Parquet
GeoParquet-style files with WKB geometry
GeoJSON extracts through the official Python tool
GeoJSON sequence and other tool-supported regional outputs
Cloud object storage partitions organized by theme and type
Access methods
Amazon S3 official release paths
Microsoft Azure Blob Storage official release paths
Official Overture Maps Python CLI
DuckDB and SQL-based cloud querying
Overture Explorer for inspection and small-area downloads
QGIS and ArcGIS workflows documented by Overture
Partner mirrors including BigQuery, Databricks, Snowflake, Fused, and Wherobots; these may lag official releases
Quality and limits
Coverage is not uniform across countries, themes, feature types, or source providers.
Source licenses, attribution obligations, and redistribution terms differ across themes and providers.
Base features are translated from upstream sources without a conflation process, so their completeness and accuracy mirror those sources.
Places uses multi-source conflation and confidence information, but conflation does not make every record authoritative.
Monthly releases do not guarantee that every upstream feature is current.
Public release files are retained for a maximum of 60 days according to Overture's documentation, so reproducible projects should archive the exact inputs they use.
Overture is not a universal cadastral, parcel, address, building-permit, infrastructure-ownership, or real-time operational database.
GERS identifiers and bridge files are theme-dependent; they should not be assumed to exist for every feature class.
Analysis workflows
Select the relevant theme and feature type for the geographic question.
Discover the exact release through the official release calendar or STAC catalog and record the release identifier.
Filter cloud data by theme, type, bounding box, and required columns before downloading or querying.
Inspect schema fields, geometry types, source metadata, identifiers, confidence fields, and license information.
Use DuckDB or another spatial SQL engine for regional filtering, joins, counts, proximity analysis, and aggregation.
Use the official Python CLI to create smaller GeoJSON or GeoParquet extracts for desktop GIS and application workflows.
Load regional extracts into QGIS, ArcGIS, GeoPackage, or another analysis environment for cartography and inspection.
Reproject into an appropriate local coordinate system before calculating distance, area, density, or network-related measurements.
Validate important features against imagery, official local GIS, field observations, or domain-specific authoritative sources.
Archive the exact files, release identifier, schema version, query or download parameters, attribution text, and validation notes for reproducibility.
Value inside EDK
What Overture Maps contains
Overture's current schema documentation organizes the data into six themes: addresses, base, buildings, divisions, places, and transportation. These themes cover different parts of the physical-world information stack rather than duplicating a single map layer. Addresses support address-oriented records; buildings represent structures; places represent physically identifiable destinations and entities; transportation supports roads and other movement-related features; divisions represent geographic and administrative areas; and base includes categories such as land, water, infrastructure, land use, land cover, and bathymetry. (docs.overturemaps.org)
The project is particularly useful when a workflow needs several feature classes represented through a common data model. For example, an analyst might combine place points with building polygons, address records, transportation segments, and administrative boundaries. Overture's documentation also describes Global Entity Reference System identifiers, or GERS IDs, which can support joins and feature tracking in themes where those identifiers are available. They are not universal across every theme: the base guide explicitly states that base features are not included in the GERS registry. (docs.overturemaps.org)
- •Themes: addresses, base, buildings, divisions, places, and transportation.
- •Common use cases: map layers, place search, geocoding support, routing preparation, spatial joins, regional summaries, and location-data products.
- •Feature detail varies by theme, source, country, release, and feature type.
- •Overture is not a guarantee of authoritative parcel, address, road, building, or regulatory data for every jurisdiction.
Geography, temporal coverage, and update cadence
Overture is designed for broad geographic coverage, including global map data in several themes, but “global” does not mean every location has the same feature completeness, attributes, positional accuracy, or update frequency. Data quality depends on the source and on the theme's processing method. The base theme is described as a pass-through translation of source data without conflation, so its known quality issues follow the upstream datasets. Places, by contrast, combines multiple sources through a conflation pipeline and documents source-level licenses and coverage. (docs.overturemaps.org)
Overture has released data monthly since October 2023. Its release tags use a date-based format such as 2026-08-19.0, and the release calendar describes both data and schema versioning. On September 9, 2026, the latest documented release was 2026-08-19.0, with a proposed 2026-09-23.0 release listed next. Proposed dates can change, so production workflows should discover the release actually available rather than hard-code a future date. (docs.overturemaps.org)
- •Release cadence: monthly, with occasional major schema changes planned quarterly.
- •Latest documented release on September 9, 2026: 2026-08-19.0.
- •Feature freshness is not necessarily the same as release frequency; upstream sources may update on different schedules.
- •Archive or mirror the exact files needed for a regulated, scientific, or reproducible workflow.
Formats, access methods, and licensing
Overture publishes cloud-native Parquet data partitioned by theme and type rather than one “entire planet” file. The official data repository documents Amazon S3 and Microsoft Azure paths for current releases. The files use GeoParquet conventions: geometry is encoded as well-known binary, and the data includes a bounding-box structure that can support more efficient spatial filtering in cloud queries. (github.com)
Users can access the data directly from cloud storage, query it with engines such as DuckDB, use the official Overture Python command-line tool, inspect areas in Overture Explorer, or use documented integrations and mirrors. The official documentation identifies access routes involving QGIS, ArcGIS, BigQuery, Databricks, Snowflake, Fused, and Wherobots, although partner mirrors are community-maintained and may lag the official release. (docs.overturemaps.org)
- •Primary formats: Parquet and GeoParquet-style files with WKB geometry.
- •Official access: Amazon S3 and Microsoft Azure Blob Storage.
- •Other access: Python CLI, DuckDB, Overture Explorer, GIS integrations, and partner mirrors.
- •Licensing: inspect theme- and source-specific attribution before redistribution or commercial use.
A defensible GIS workflow with Overture Maps
Start by defining the geographic question and selecting the smallest relevant theme and feature type. A request such as “find schools near residential roads” may require places, transportation, and possibly buildings or divisions; downloading every theme for an entire continent is usually unnecessary. Use a bounding box or spatial predicate early, and retain the release identifier in the project metadata.
Next, inspect the schema and source information before analysis. Check geometry type, coordinate reference system, identifiers, source fields, confidence or quality fields where available, and whether the feature is derived through direct translation or conflation. Do not assume that similarly named attributes mean the same thing across themes. For example, a place point, a building polygon, and an address record describe related but distinct physical-world concepts.
- •Choose theme and type before downloading.
- •Filter by bounding box and columns as early as possible.
- •Preserve release, schema, source, license, and attribution metadata.
- •Use projected coordinates for distance, area, and density calculations.
- •Validate operational results against authoritative local or domain-specific sources.
Where Overture fits in the wider location-data ecosystem
Overture is best understood as a normalized, open distribution and schema layer for important categories of map data. It can reduce the engineering work required to ingest several external sources, represent them in a consistent theme structure, and query them in cloud-native formats. That makes it complementary to datasets such as OpenStreetMap Planet, OpenAddresses, satellite imagery archives, elevation models, hydrography, census boundaries, and environmental observations rather than a replacement for all of them.
For a world-model or physical-world computation workflow, Overture can provide concrete geographic entities and relationships: a building near a road, a place within a division, an address associated with a destination, or transportation features crossing a region. Those relationships can support search, filtering, ranking, proximity calculations, regional aggregation, and change-aware data pipelines. The important limitation is scope: Overture does not itself provide every type of physical feature, every observation time, or every authoritative local record. It should be combined with other datasets when the question involves hazards, permits, service requests, crime, vegetation condition, weather, imagery, infrastructure ownership, or current operational status.
- •Strong as a common map-data foundation and cloud-native interchange layer.
- •Complementary to imagery, environmental data, public records, census data, and authoritative local GIS.
- •Useful for geographic joins and computation, but not sufficient by itself for every operational question.
- •Treat the release and source metadata as part of the dataset, not as optional documentation.
Questions teams ask
Is Overture Maps one dataset or several datasets?
It is better understood as a multi-theme dataset ecosystem. Overture organizes data into addresses, base, buildings, divisions, places, and transportation, then further partitions releases by theme and feature type. There is no single Overture file containing the entire planet. (github.com)
How often is Overture Maps updated?
Overture publishes monthly data releases. The release calendar says releases are date-tagged and documents a history of monthly releases since October 2023. As of September 9, 2026, the latest documented release was 2026-08-19.0. Monthly publication should not be interpreted as a guarantee that every upstream feature was updated during that month. (docs.overturemaps.org)
What format does Overture Maps use?
The official distribution uses cloud-native Parquet files, including GeoParquet-style geometry encoded as WKB. Data is partitioned by theme and type and is available from Amazon S3 and Microsoft Azure. The official Python tool can produce GeoJSON or GeoParquet extracts for selected bounding boxes. (github.com)
Is Overture Maps free to use?
The data is openly distributed, but “free” does not mean that every theme has identical terms. Licensing and attribution vary by theme and source. Base and transportation include OpenStreetMap-derived content under ODbL, while the places theme lists multiple source licenses, including CDLA Permissive 2.0, Apache 2.0, and CC0 1.0. Review the applicable attribution and license documentation before redistribution or commercial use. (docs.overturemaps.org)
Can Overture Maps replace local authoritative GIS data?
Not in general. Overture can provide broad, structured reference data and is useful where local data is unavailable or difficult to integrate. However, the project documents source-dependent quality and coverage limitations. For property, engineering, emergency response, regulatory, or operational decisions, validate Overture features against the authoritative local or domain-specific source.
Keep exploring
openstreetmap planet
OpenStreetMap is a major upstream and complementary source for roads, paths, buildings, land use, waterways, infrastructure, and other mapped features. Comparing the full planet extract with Overture's normalized themes helps explain source translation, schema normalization, and coverage tradeoffs.
google open buildings
Google Open Buildings provides machine-detected building polygons for selected regions and is a useful comparison for building coverage, model-derived features, validation, and the limits of treating mapped structures as a complete building inventory.
Sources
Overture Documentation: Schema Reference
Official reference for Overture's six themes, schema organization, and shared data-model concepts. ([docs.overturemaps.org](https://docs.overturemaps.org/schema/?utm_source=openai))
Open sourceOverture Documentation: Releases
Official release cadence, current release information, versioning, proposed schedule, and data-retention policy. ([docs.overturemaps.org](https://docs.overturemaps.org/release-calendar/?utm_source=openai))
Open sourceOverture Maps Data Repository
Official distribution paths, Parquet and GeoParquet details, partitioning, release discovery, and cloud access information. ([github.com](https://github.com/OvertureMaps/data?utm_source=openai))
Open sourceOverture Documentation: Attribution and Licensing
Official theme- and source-level licensing and attribution requirements. ([docs.overturemaps.org](https://docs.overturemaps.org/attribution/?utm_source=openai))
Open sourceOverture Documentation: Official Data Access and Mirrors
Official documentation hub covering S3, Azure, Python tooling, DuckDB, QGIS, ArcGIS, and partner access routes. ([docs.overturemaps.org](https://docs.overturemaps.org/?utm_source=openai))
Open source