Felt

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This isn't just another feature update – it's a fundamental shift in how teams can work with spatial data. Felt SQL queries work across all your cloud sources including PostGIS, Snowflake, Databricks, Redshift, BigQuery and Microsoft SQL Server. No more context switching, no more data silos, no more compromises. Connect, query and share.

We're thrilled to introduce SQL queries in Felt, putting the full power of your database directly at your fingertips. ✌️ For years, teams have trusted Felt to build maps, apps, and dashboards that bring spatial insights to life. Now, we're taking that capability to the next level. With SQL queries, you can tap directly into your data warehouse and craft custom queries within the Felt environment you already know and love.

The best part? We’ve built in tons of workflow enhancements into Felt SQL queries to make it easy for anyone to jump in and build off existing queries. This is spatial data analysis as it should be: powerful, intuitive, and accessible for the whole team to dive in as needed.

@SustGeoLove Love to hear you’ll be taking advantage of this in your workflows!

@felt Felt's update is a significant step forward for collaborative GIS! New data-associated comments feature will enhance our project workflows.

The best collaborative GIS tool just got even better. 🚀 Data-associated comments are live in Felt! You can now comment directly on vector and raster features, move your comments around by dragging, open features from comments, and create comments from clicked features. #gis

Tired of rigid admin boundaries? Use H3 for a more precise spatial analysis! Visualize your data in H3 bins in a few simple steps: • Upload to Felt • Select H3 • Done! See it in action ⤵️ #SpatialAnalysis #DataVisualization #GIS

Exploratory spatial data analysis tools are essential for visualizing and analyzing spatial data, helping uncover valuable insights. For instance, our table view feature enables users to thoroughly examine a dataset, sort attributes, and choose features to display on the map. 🗺️

🐍 Our Python SDK is tailored for effortless interaction with Felt's API. With familiar syntax and conventions, developers can now harness Felt's power while saving time and reducing effort. Explore the library here: github.com/felt/felt-pyth… #data #map #gis #python #api

Learn how to publish @QGIS maps to the web with the ‘Add to Felt’ plugin. youtu.be/-mUdqQ4FX6E Styled rasters and vectors import seamlessly! 🗺️ #GIS #GISchat

Have you tried Felt's Extract tool yet? Extract let's you build any boundary polygon (buildings, neighborhoods, counties – event states!) directly from the basemap – no external datasets needed. Pro tip: hold down the Shift key to select multiple polygons simultaneously!

Is your team blocked when it comes to accessing spatial insights? It takes minutes to configure a Felt dashboard, and even less time for teams to intuively find the insights they need. Now everyone can run powerful queries and get stats at -a-glance.

Do your New Year's resolutions include trying out our new JavaScript SDK? Here are five fun ideas to get the juices flowing before January: - Take a map and remove the UI, then build a branded experience - Finally integrate a map into that dashboard you've been building - Filter data from a dashboard and apply those filters to a map - Create an interactive scrolling experience that's never been seen before - Flip through the dev docs with a cup of cocoa and dream ✨

We all need help focusing sometimes. Set map constraints in just a few clicks so your viewers stay on task.

@patricktrack @tacobell @mamataakella We got you: felt.com/map/Think-outs…

@felt @tacobell @mamataakella Need this! But can’t DM you

Traveling for the holidays? Don't leave town without optimizing your route for proximity to @tacobell with this deeply technical analysis from our own super fan and cartographer @mamataakella 🌮 🌯 Message us and we will send you the link :)

Show us your EOY toolbar, QGISers! If it doesn't have Felt's plugin, you've been missing out! We want QGIS users to have best-in-class tools at their fingertips, and that's why we built the lightning fast plugin with our friends at @northroadgeo to instantly visualize your #QGIS maps on the web.

Our H3 tiles render instantly and it’s all thanks to Tippecanoe – Felt's open-source geodata pre-processing tool that optimizes visual appearance across data densities and zoom levels to deliver fast web map tiles. Tippecanoe dynamically assigns points to H3 bins as tiles are served, calculating aggregate statistics for each point at every zoom level. This eliminates static binning, enabling lightning-fast, real-time summary calculations across all zoom levels. Learn more: github.com/felt/tippecanoe