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Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care. You can simply create spatial analytics and data mining applications and run them in any cloud environments.
Features
- Set up Scala and Java API in 5 minutes with Maven and SBT
- Python and R API are also available on PyPI and CRAN
- Low Memory Consumption
- High Speed
- Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems
- Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care
Project Samples
