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...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.

The Base Application Template has been created to aid PHP developers by providing query debugging, query execution times, page load times, peak memory usage per page, debug data for post, get, cookie, server, environment and session variables, ability to include custom debug data and faster development time using the provided query function which requires less coding. This framework may be used in commercial or non-commerical projects. You can also find the latest version on github : https://github.com/rizkhan7/bat