The Most scalable spatial analytics database engine
Efficiently Linking Enterprise Data
SedonaDB facilitates efficient and seamless linking of enterprise data to a wide array of open spatial data sources, including essential categories like map data, roads, buildings, natural events, and man-made events.
SedonaDB seamlessly connects your data with leading data warehousing solutions like Snowflake and Redshift, as well as data lakehouses like Databricks and OLTP databases such as Postgres/PostGIS, maximizing your data’s potential.
Scalable Spatial Data Processing
SedonaDB innovatively separates the spatial processing and analytics layer from the data storage layer while implementing a scalable out-of-core spatial computation model through a distributed system architecture.
A spatial lakehouse solution, powered by Havasu
SedonaDB provides an Apache Iceberg compatible spatial table format (namely Havasu) that enables efficient querying and updating of geometry and raster columns on parquet files in object stores (such as AWS S3).
Self-managed / provisioned service
Users do not need to spend time and money managing cloud/compute resources for SedonaDB. Instead, users save time and money focusing on the spatial analytics task necessary for their business use case.