{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Programming Tech Brief By HackerNoon","title":"How to Perform GIS Computations on Non-GIS Databases","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/e115d22c\"></iframe>","width":"100%","height":180,"duration":743,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/how-to-perform-gis-computations-on-non-gis-databases.\nIf your backend storage doesn't natively support spatial queries, this article is tailored for you.\nCheck more stories related to programming at: https://hackernoon.com/c/programming.\n            You can also check exclusive content about #programming-tutorial, #geospatial, #k-nearest-neighbor, #gis-computations, #non-gis-databases, #google-maps, #hackernoon-top-story, #geo-indexing,  and more.\nThis story was written by: @joellopes. Learn more about this writer by checking @joellopes's about page,\n            and for more stories, please visit hackernoon.com.\nIf your backend storage doesn't natively support spatial queries, this article is tailored for you. You can always build another microservice to handle spatial data, but this option often involves the overhead of maintaining an additional application. Another approach is to use geo-indexing libraries like S2 and H3. S2 divides the sphere into cells, each with a unique 64-bit identifier. Higher levels correspond to finer resolutions and smaller cell areas.","thumbnail_url":"https://img.transistorcdn.com/KhCapPSRkLGL2Xw8888yuChkNRWthaKapLYTvNdu4W4/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMTY2LzE2ODM1/ODIzMzAtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}