CartoDB for schools is great!
We use CartoDB at George Mason University to teach students about location intelligence and GIS. The only problem we're addressing is …
Overview
What is CARTO?
Carto (formerly CartoDB) in Brooklyn, New York offers their location intelligence solution.
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What is CARTO?
Carto (formerly CartoDB) in Brooklyn, New York offers their location intelligence solution.
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- No setup fee
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- Free Trial
- Free/Freemium Version
- Premium Consulting / Integration Services
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Alternatives Pricing
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What is ArcGIS?
Esri in Redlands, California offers ArcGIS, a geographic information system.
Product Demos
Demo - CartoDB (Data Innovation Day 2014)
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carto demo 3d slam KITTI 2019 08 13 16 26 16
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Carto Demo Playthrough / Longplay / Walkthrough (no commentary)
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Carto Maps Demo for temporal animation, and multiple attribute data
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EZvi Tank Changing the Carto Demo
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Data Viz Workshop: Carto demo 1
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Product Details
- About
- Tech Details
What is CARTO?
CARTO Video
From smartphones to connected cars, location data is changing the way we live and the way business happens. CARTO is the platform that turns location data into more efficient delivery routes, better behavioral marketing, strategic store placements, and much more.
Everyone, f...
 Show More CARTO Technical Details
| Operating Systems | Unspecified |
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| Mobile Application | No |
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Reviews and Ratings
(7)Reviews
(1-4 of 4)Companies can't remove reviews or game the system. Here's why
August 07, 2017
CartoDB for schools is great!
We use CartoDB at George Mason University to teach students about location intelligence and GIS. The only problem we're addressing is exposing students to a platform that can help them make charts/maps easily and visualize geographic data for their theses and dissertations.
- Twitter data imports
- Connectors for various data sources (GDrive, CSV, etc)
- Basemaps of different types
- I don't like the new Builder UI as it has been tough to explain. Other than that I have no complaints.
- It has removed the barrier to entry for GIS tools.
December 09, 2016
CartoDB - Great tool for geospatial data viz
As an analyst at an economic development consulting firm, I frequently analyzed and visualized demographic data. My organization did not use CartoDB as a whole, but analysts were allowed to use whatever tools they wanted to produce work, and so I decided to use CartoDB because of its ease of use. I primarily used the software to generate chloropleth maps to visualize different pieces of demographic data across zip codes. Without CartoDB, we typically made these maps manually or using other software that didn't have as much visual customization as CartoDB.
- SQL integration - CartoDB supports SQL, so you can use SQL to do different types of data munging and analysis, which makes it easier to do more complex visualizations of data than just using the column/row interface. It also uses common programming data structures (string, float, etc.) which makes it easy to parse data types.
- GEOJSON compatibility - The software comes out of the box with common maps that you might want to use, but you can upload your own GIS or GEOJSON files to create custom maps.
- Out of the box visuals - The default settings/options for map creation over most of the bases of what you might want to do. The out of the box color schemes and design are great.
- Learning curve - CartoDB might be difficult to use if you don't have a bit of SQL or data structures background. If you're not familiar with floats, strings, etc., you might upload an Excel file and be confused about how to manipulate it to get the software to create the maps that you want.
- Performance - When I used it, there were some occasional issues with loading and parsing large data files.
- CartoDB definitely saves a lot of time when creating visualizations. Previously, I would use different software and have to make edits manually (or just create the visualizations manually to start with). I would say that the software definitely cuts the time required to create certain visualizations by a half or two-thirds.
- Tableau and python
Python is definitely a more powerful tool for data munging and analysis, but the python packages for geo-related data viz (bokeh, matplotlib, seaborn) are cumbersome to use. I would recommend doing your data analysis in Python and then exporting the final data to CartoDB for visualization. One benefit of doing this is that CartoDB can automatically publish your viz to a link or object, so you don't have to export it and host it yourself. Another benefit is that CartoDB automatically updates the viz once you change the data, eliminating the need to continuously regenerate image files.
I haven't used Tableau too extensively, but from the experience I've had with it -- Tableau is better suited for traditional analytical visualization (charts, graphs, etc.) than for geospatial mapping and visualization.
I haven't used Tableau too extensively, but from the experience I've had with it -- Tableau is better suited for traditional analytical visualization (charts, graphs, etc.) than for geospatial mapping and visualization.
May 31, 2016
CartoDB is a joy to work with
I integrated CartoDB into a Java Spring MVC web application to support complex visualizations of geographic networking data. CartoDB allowed me to create maps of network nodes colored by various state information to help identify and diagnose trouble areas. Once I got it set up it was very simple to add visualizations of additional metrics so we ended up building out map styles for all sorts of information and finding interesting and unexpected patterns.
- It is amazing at allowing control of the visualizations. It takes a little bit to get used to but the combination of full SQL queries and CSS-like styling is very powerful.
- The services are built on a robust stack of open source software. I was able to build a standalone instance of CartoDB relatively easily (after some research and trial and error).
- Server side map rendering is key for handling large data sets. The way the images are returned makes them very easy to catch in an HTTP cache to minimize the hits to the server. The interactivity that CartoDB has built in makes this completely transparent to the end user, they can click on parts of the static images and be presented with popups or change map styles. It's a very clever implementation.
- I adopted CartoDB just before a major API change. We chose to make a standalone instance and unfortunately this API change meant we would have to do a lot of work to move to a newer version. Perhaps just a hazard of being an early adopter.
- It would be extremely helpful if CartoDB provided a Java library for interacting with the service. The visualization definition (setting up the map, styles, etc) is all handled by sending a JSON structure to the service. In my application I had to manually create a large number of Java classes mapping the expected JSON format so that we could construct the visualization from our code. This was a fair amount of work and was invalidated when CartoDB later changed their visualization structure. This could be mitigated by providing client libraries for common languages.
- There's an immediate "wow" factor to using CartoDB. It's what you want a map to look like and provides very intuitive user functionality out of the box. I demoed our mapping capabilities to a set of network operators and by the end of the call they were begging for an upgrade to their deployed systems.
- The hosted service is reasonably priced but with some work you can build your own standalone instance. At that point you have a "free" (not counting development time) mapping solution that can be installed in private networks, something not possible with Google Maps.
- I had a hard requirement that we not send actual data to Google. We were allowed to request the base map tiles from Google but the customer did not want their position data sent outside of the network. CartoDB made this possible since the overlay tile renderer was installed internally. This was a crucial selling point that helped us win the business.
- Google Maps API and Google Fusion Tables
Google Maps API was what we started with. It provides a lot of nice tools, but they are all browser-side. This means that when you want to display points on a map you send data to the users browser and the software runs on the users's machine to render that data into points. This allows flexibility and more dynamic behavior but does not scale to large numbers of data points - more than ~1000 points brings the browser to its knees. CartoDB takes a fundamentally different approach, rendering position data on the server side into static image tiles that are overlaid on top of a standard Google Map. This means scaling is dependent on backend equipment not on the user's browser/machine.
If you're doing something small Google Maps API is great and it doesn't require any extra setup or dependencies. If you need to scale CartoDB is the best solution available.
If you're doing something small Google Maps API is great and it doesn't require any extra setup or dependencies. If you need to scale CartoDB is the best solution available.
April 11, 2016
CartoDB is great!
Currently CartoDB is not being used by our company internally. Though there has been some talk of eventually doing so. We use for CartoDB as a tool to create interactive online web maps that accompany environmental documents we produce.
- Simiple UI.
- Great learning library full of videos.
- Professional quality cartography.
- The ability to easily customize legends like color swatch shape / size is missing.
- When you turn on the option for "mouse scroll wheel zoom" the system should automatically turn on the "Full Screen" mode as well. Because the scroll wheel zoom only works in full screen view.
- More visualization templates.
- We ended up winning a pretty large job that we used CartoDB to implement. So I would say that was a positive.