Apache Sedona (formerly GeoSpark) is a cluster computing system for processing large-scale spatial data. It extends Apache Spark / SparkSQL with a set of out-of-the-box Spatial Resilient Distributed Datasets (SRDDs)/ SpatialSQL that efficiently load, process, and analyze large-scale spatial data across machines. Apache Sedona joins Apache Software foundation in July 2020.
I implemented Apache Sedona into Apache Spark and SparkSQL. Project website: sedona.apache.org
Apache Sedona is the defacto spatial data processing framework on top of Apache Spark.
Apache Sedona has 300K monthly downloads.
Users and contributors include Facebook, Apple, Uber, MoBike, and numerous startups
Apache Sedona in production (video), from Gyana, a British Location Inteligence company
Apache Sedona received an evaluation from PVLDB 2018 paper How Good Are Modern Spatial Analytics Systems?, written by Varun Pandey, Andreas Kipf, Thomas Neumann, Alfons Kemper (Technical University of Munich), quoted as follows:
GeoSpark comes close to a complete spatial analytics system. It also exhibits the best performance in most cases.
Apache Sedona is a full-fledged big geospatial data analytics system that provides
- Data generation (GeoSparkSim, MDM 2019)
- Data managemenet and query processing (GeoSpark, Geoinformatica 2019)
- Visulization (GeoSparkViz, SSDBM 2018, an extended version is under revision by VLDB Journal)