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Head-to-head · Spatial Databases

GeoMesa vs rasdaman

  • Updated Oct 2026
  • Both researched from official sources
  • 4 checks side by side
Higher score GeoMesa #2 in Spatial Databases 9.2/10 Open source ✓ 2 of 3 features Visit GeoMesa
rasdaman #3 in Spatial Databases 9.0/10 Free plan Free plan✓ 3 of 3 features Visit rasdaman

GeoMesa leads on 0 checks, rasdaman on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreGeoMesa · 9.2/10
  • Free planonly rasdaman
  • Most featuresrasdaman · 3 of 3

GeoMesa scores higher on our rubric for spatial databases: 9.2 against 9.0 out of 10; our editors rank them #2 and #3.

GeoMesa is the better fit for distributed spatio-temporal workloads. rasdaman is the better fit for large-scale raster and multidimensional data.

  • GeoMesa fits best

    Distributed spatio-temporal workloads

  • rasdaman fits best

    Large-scale raster and multidimensional data

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Side by side

Feature GeoMesa 9.2/10 Visit ↗ rasdaman 9.0/10 Visit ↗
At a glance
Editor score 9.2 9.0
Ranking #2 in Spatial Databases #3 in Spatial Databases
Best for Distributed spatio-temporal workloads Large-scale raster and multidimensional data
Pricing model Free Free plan + paid
Starting price Open source —
Free plan Not checked yet ✓ (best)
Free trial — —
Deployment Self-hosted Self-hosted
Support Email, Community, Docs Email, Community, Docs
Integrations 13 integrations 13 integrations
Built for Mid-market, Enterprise Small business, Mid-market, Enterprise
Features GeoMesa 2/3 · rasdaman 3/3
Raster support Not checked yet ✓ (best)
3D geometry support ✓ ✓
Coordinate transforms ✓ ✓
Specs
Deployment model Self_hosted Self_hosted
Query interface Sql Sql
Spatial data types point, multipoint, linestring, multilinestring, polygon, multipolygon, geometry collection, geometry multidimensional arrays, raster data, geo coverages, 3D and 4D arrays
Our review
Pros
  • Specialized Z2, Z3, XZ2, and XZ3 spatio-temporal indexes
  • Distributed spatial queries across point, line, and polygon data
  • Kafka streaming plus Spark and Spark SQL analytics
  • SQL-like rasql queries support raster retrieval and manipulation
  • OGC services include WCS, WCPS, WCS-T, and WMS
  • Integrates with Python, R, QGIS, GDAL, ArcGIS, and more
Cons
  • Self-hosted deployment requires teams to operate the environment
  • Its architecture depends on distributed data-system components
  • Raster support is outside the documented feature set
  • Self-hosted deployment requires Linux or API-based operation
  • Parallel processing and caching are limited to the enterprise edition
  • The feature set is specialized for raster and array workloads
Our verdict

GeoMesa is an Apache-licensed, open-source suite for storing, indexing, querying, transforming, and analyzing large spatio-temporal datasets. It is designed for organizations working with high-volume point, line, polygon, and time-aware…

Read the review →

rasdaman is an open-source multidimensional array database for storing, querying, and processing raster data, datacubes, geo coverages, and 3D or 4D arrays. It is aimed at teams working with satellite imagery, sensor time series, climate…

Read the review →
  1. GeoMesaSpatial Databases 9.2Open source
  2. rasdamanSpatial Databases 9.0Free plan

Strengths and trade-offs

  • GeoMesa — where it wins

    • Specialized Z2, Z3, XZ2, and XZ3 spatio-temporal indexes
    • Distributed spatial queries across point, line, and polygon data
    • Kafka streaming plus Spark and Spark SQL analytics

    Where it doesn't

    • Self-hosted deployment requires teams to operate the environment
    • Its architecture depends on distributed data-system components
    • Raster support is outside the documented feature set

  • rasdaman — where it wins

    • SQL-like rasql queries support raster retrieval and manipulation
    • OGC services include WCS, WCPS, WCS-T, and WMS
    • Integrates with Python, R, QGIS, GDAL, ArcGIS, and more

    Where it doesn't

    • Self-hosted deployment requires Linux or API-based operation
    • Parallel processing and caching are limited to the enterprise edition
    • The feature set is specialized for raster and array workloads

More comparisons

All spatial databases comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update