This is a similar view as the Google Fusion Table map at the top of the page. I almost feel guilty about that, this is a great company and service and I like to support the tools that I use in my business. As of writing this I have paid Mapbox exactly nothing. Although Mapbox documentation is good, it would be helpful to have more high-level “getting started” like articles for non-GIS professionalsįrom an account and cost perspective, evaluating Mapbox and creating my first maps was very straightforward.Even something as simple as the line number that contained the fault would save so much pain for end users. Upload errors contain no helpful details.Mapbox’s upload utility is picky about the data that is being uploaded, and often fails for simple reasons like a missing lat or long value.Uploading data is limited to 5MB per file, so larger datasets need to be split into multiple files.While not nearly as extensive as the Google ecosystem, there are enough experienced Mapbox freelancers that you should be able to get help when you need it.Mapbox as a company is constantly adding new features and innovations.The Mapbox Studio is feature rich and well-implemented.Mapbox has excellent documentation and support. The use of “map loads” rather than tile loads makes understanding your usage and costs understandable and predictable (the first 50k map loads are free).Mapbox has an actual free tier with enough functionality and resources to create and serve business-ready maps at no cost for small businesses.These are the pros and cons I discovered while using Mapbox: It is somewhat complicated to learn, but Mapbox has good documentation and helpful support so this is doable for non-experienced users The Mapbox Studio is a full-featured map styling tool. There is a limit on total disk space you can use on their servers, but the limits are in the tens of gigabytes which should be plenty for any small business to get started with. Create as many data sets, tilesets, and maps as you want. Mapbox makes it easy to dive into their technology and experiment with it with few restrictions. While the workflows from these two companies don’t sound that different based on the summaries given above, in practice they are very different, from the capabilities of each to the pricing. You then upload the tileset to Maptiler Cloud where you apply it to a map and apply custom styles, similar to Mapbox. Rather than upload your data set, you instead download the Maptiler Desktop application and process your data into a tileset on your local machine. With Maptiler you are getting a similar result – an OpenStreetMap with your custom data and styles – but with a different workflow. The end result is a map that is based on OpenStreetMap, with your data layer (or layers) rendered as tiles and any custom styling you have created. You upload your data, convert that data to a map tileset, apply that tileset to one of Mapbox’s default map styles, then customize the style in Mapbox Studio. Mapbox is more similar to Fusion Tables in terms of workflow. While each company essentially sells the same end result – map hosting services that can serve large data sets as tiled maps – each delivers their products very differently. In the end I concluded two companies offered products that matched my needs: Mapbox and Maptiler. I spent a lot of time researching and testing available services and technologies. The goal here is to visualize large datasets on interactive maps with the lowest possible cost and difficulty. It is my goal to evaluate map technology providers from the perspective of a webmaster, not a GIS professional or programmer. Technologies outside of the Google ecosystem are largely geared towards GIS professionals, with little documentation or tools that help non-GIS people get started quickly and easily. Mapping a lot of data was easy with Fusion Tables, so I was shocked to find just how difficult competing products would be. Fusion Tables is being discontinued so I needed to find an alternative for mapping large datasets. More importantly, Fusion Tables rendered the data layer on the map on the server side, eliminating the inevitable performance issues on client machines that made mapping large datasets difficult or impossible This is what 2,715 data points looked like mapped with Google Fusion Tables. For those unfamiliar with Fusion Tables, it was a product that allowed for fast and easy rendering of large datasets on Google Maps.įusion Tables was easy to use, and allowed website owners to display many thousands of placemarks quickly and easily. The impetus for the comparisons made in this article was Google’s announcement that they were discontinuing their Fusion Tables product.
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