Kent Marten

Our team started on Geospatial journey with Databricks DBR 16.X, from legacy project migration and continued to expand by ingesting and processing three different geospatial datasets (HD USHR maps, public OSM and curated OSM (Overture)). We applied different optimization techniques to make spatial joins more performant and worked closely with Databricks Geospatial team in testing out incremental improvements in DBR, culminating in large scale performance increase on DBR 17.X bringing support to geospatial data types (GEOMETRY, GEOGRAPHY) as dedicated data types that could be stored in delta table. A significant optimization was observed in spatial joins, which could eliminate previously used optimization techniques, making data pipelines maintenance easier. All of these improvements enabled us to enrich internal datasets based on various road attributes from these datasets and use them in analytics, training and potential reinforcement learning applications where needed.

Spatial data has always been important and working with it has always been complex. Until now. In this session we'll discuss simplified approaches for working with spatial data, highlighting new performance benchmarks that demonstrate how Databricks Spatial SQL scales spatial workloads, and what this means for real-world use cases. You'll also hear about customer stories and key partner integrations that shape how leading organizations are maximizing the value from location-based data. This session will wrap up with a look at the latest roadmap updates.

Spatial data is increasingly important, but working with it can be complex. In this session, we’ll explore how Databricks SQL supports spatial analysis and helps analysts and engineers get more value from location-based data. We’ll cover what’s coming in the Public Preview of Spatial SQL, when and how to use the new Geometry and Geography data types, and practical use cases for H3. You’ll also learn about common challenges with spatial data and how we're addressing them, along with a look at the near-term roadmap.

Databricks SQL has added significant features in the last year at a fast pace. This session will share the most impactful features and the customer use cases that inspired them. We will highlight the new SQL editor, SQL coding features, streaming tables and materialized views, BI integrations, cost management features, system tables and observability features, and more. We will also share AI-powered performance optimizations.