I will be conducting the Spatial SQL workshop at MAC URISA 2018 in a few weeks. Offered as a full day workshop and as an optional half-day workshop for the basics, you will be introduced to SQL, PostgreSQL and PostGIS, and walked through several exercises on how to perform spatial analysis using SQL. The workshop will take place on October 24th, at Resorts Casino and Hotel, in Atlantic City, NJ.
With 31 in attendance, we had a full room during the pre-conference workshop day at MAC URISA 2016. I received some good feedback from the attendees and asked them to reach out to me if they have any questions about the materials after the session is over.
We also touched upon some additional steps one could take working with ArcGIS and PostgreSQL. Seth Docherty was a great help in demonstrating how we could move GIS data, such as shapefiles and geodatabase feature classes, into a PostGIS-enabled database and begin using it with ArcGIS. There are a few caveats, which I will detail in a later post.
Thank you again to all of the MAC URISA 2016 workshop attendees. If you were unable to make it to the workshop, feel free to browse the materials at the link above. Feel free to reach out to me if you have any comments, questions, or feedback on the materials.
In my experience using ArcGIS with PostgreSQL, the support has gotten better and considerably more stable over the years. While I haven’t tested every permutation of ArcGIS, PostgreSQL and PostGIS, you should be safe to use the various components together, as long as you are close to the “official” version. Of course, stick to what is recommended if you are using PostgreSQL in production, especially if you may need support from ESRI.
Naturally, if you are not tied to the ESRI stack, you are more free to choose the PostgreSQL version you would like to use. While I’ve not yet upgraded to PostgreSQL 9.6, I am looking to do so by the end of the calendar year.
GIS users deal with large, complex data. However, many GIS users still rely on shapefiles or other antiquated forms of vector data. Even ESRI’s “new” file geodatabase lacks the functionality you get from a true DBMS. Creating your own database server can be a daunting task. Even if you set one up and load your data, you are just scratching the surface of what is possible.
Learn Spatial SQL will help guide you through implementing your own database system, as well as demonstrating how much of your regular GIS workflow can be incorporated directly into your database, using SQL.
While many DBMSs are expensive, one of the best, fully-featured database systems today is the free and open source PostgreSQL. Coupled with the PostGIS extension, you can manage immense data sets and perform complicated tasks all through SQL.
Beginners, fear not. While we will go into advanced topics, this blog will strive to be as approachable and inclusive as possible.