Query billions of rows in seconds. Process terabytes of Parquet data. Run complex spatial analysis locally without a database server. This is the future of geospatial analytics.
The analytical database engine built for modern data workloads
Extend capabilities with specialized extensions
Full geospatial support with GEOS-powered geometry operations and spatial indexing.
Query data directly from cloud storage without downloading entire files.
Query Apache Iceberg tables for data lakehouse analytics.
Read Delta Lake tables with ACID transactions and versioning.
Fast text search with inverted indexes and relevance scoring.
Connect to external databases and query across sources.
Built for serious geospatial analysis
Process datasets larger than memory with streaming window functions and aggregations.
Optimized join algorithms including spatial joins with R-tree indexes.
Full SQL window function support for running totals, rankings, and moving averages.
Push filters to the data source to minimize I/O and accelerate queries.
Access data wherever it lives without moving it first
Query Parquet, CSV, and JSON files directly from S3 buckets
Access Azure Data Lake and Blob Storage containers
Query data in Google Cloud Storage buckets
Access any file via URL with range request support
Automatic partition discovery and pruning
IAM roles, access keys, and managed identities
Benchmarks on typical geospatial workloads
Benchmarks on laptop with Intel i7, 32GB RAM, NVMe SSD
DuckDB vs traditional approaches
| Capability | DuckDB (GeoAnalytics Pro) | PostGIS | Spark/Sedona |
|---|---|---|---|
| Server Required | No | Yes | Yes (cluster) |
| Setup Complexity | Zero config | Moderate | High |
| Query Parquet Directly | Yes | No | Yes |
| Offline Capable | 100% | Yes | No |
| Analytics Performance | Excellent | Good | Excellent |
| Spatial Functions | PostGIS Compatible | Full | Limited |
| Desktop Integration | Native | Via network | Via network |
See how DuckDB-powered analytics transforms your geospatial workflows.
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