Download to read offline
![● ArcGISAttachmentConnector
○ Powerful tool for listing
attachment details and
downloading files
● SQLExecutor
○ Easily leverage SQL queries just
as you would in Snowflake
● Keep attachments traceable - update
Snowflake table with attachment ID
● [Optional] TempPathNameCreator
○ Create temporary folder that FME
will clean up after data is loaded
Recap](https://image.slidesharecdn.com/howtomakeesriandsnowflakeworktogether-sept172025-250917172543-359e5a4c/75/Bridging-the-Gap-Between-Snowflake-and-Esri-37-2048.jpg)
![● ArcGISAttachmentConnector
○ Powerful tool for listing
attachment details and
downloading files
● SQLExecutor
○ Easily leverage SQL queries just
as you would in Snowflake
● Keep attachments traceable - update
Snowflake table with attachment ID
● [Optional] TempPathNameCreator
○ Create temporary folder that FME
will clean up after data is loaded
Recap](https://crownmelresort.com/image.slidesharecdn.com/howtomakeesriandsnowflakeworktogether-sept172025-250917172543-359e5a4c/75/Bridging-the-Gap-Between-Snowflake-and-Esri-37-2048.jpg)
Uploaded bySafe Software
Bridging the Gap Between Snowflake and Esri
Your data lives everywhere: across platforms like Snowflake, ArcGIS, and countless others. But bringing it all together? That’s where things can get messy. Formats don’t match, systems don’t talk, and moving information between them can feel like solving a puzzle with missing pieces. In this webinar, you’ll see how FME makes connecting your Snowflake and Esri data straightforward and efficient. We’ll start with a quick tour of the FME Platform so you know exactly what’s at your fingertips. Then, we’ll jump into real-world demos: connecting to dozens of formats and systems, working with geometry and geospatial data types, and moving files (including attachments) between ArcGIS and Snowflake. You’ll learn how to streamline migrations, keep datasets in sync with change detection capture, work with branch versions, load documents into Snowflake Stages, and build Esri dashboards powered by Snowflake data. We’ll also explore running spatial SQL right where your data lives, and optimizing workflows with SQL. Whether you’re integrating geospatial and tabular data, managing large-scale migrations, or automating complex workflows, you’ll leave with practical strategies to make your data work together: faster, cleaner, and without the headaches.
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Bridging the Gap Between Snowflake and Esri
- 1. Bridging the GapBetween Snowflake and Esri
- 2. Meet the Presenters Sanae Mendoza CustomerSolutions Specialist Dan Minney Customer Solutions Specialist
- 3. Welcome to Livestorm. Afew ways to engage with us during the webinar: Audio issues? Click this for 4 simple troubleshooting steps.
- 4. How to downloadslides 1. Hover over the slide deck in the webinar room 2. Click this button
- 5. Agenda 1 Introduction 2 FMEPlatform Overview 3 Data Migration & Synchronization 4 Visualizing Snowflake Spatial Data 5 Beyond Tables: Handling Documents & Attachments 6 Integrating SQL with Snowflake and Esri 7 Conclusion 8 Resources & Next Steps 9 Q&A Agenda
- 6. Poll: How do youcurrently integrate data between Snowflake and Esri?
- 7.
- 8. Unlock seamless integration betweenSnowflake and Esri using FME.
- 9.
- 10. ● Organizations increasinglyneed to combine geospatial intelligence with enterprise-scale data warehousing ● Performance, scalability, analytics, breaking down data silos ● Snowflake & Esri bring complementary strengths to the table Why Esri & Snowflake Integration Matters
- 11. Poll: Which FME capabilityis most valuable for you with Snowflake/Esri?
- 12. Snowflake Strengths ● Scalability& storage ● Integration with enterprise data ● Avoid performance slowdowns with enterprise-level queries Esri Strengths ● Advanced geospatial tools and visualization capabilities ● Cartographic mapping ● Data context (Esri specific formats, schemas, relationships, attachments)
- 13. There is abetter way, with FME! FME bridges the gap between systems with powerful, format-aware automation that makes complex data flows simple.
- 14.
- 15. The only All-Data,Any-AI Platform. FME Form FME Flow Data Movement and transformations (“ETL”) workflows are built here. Brings life to FME Form workflows FME Flow Hosted Safe Software managed FME Flow fme.safe.com/platform FME Enterprise Integration Platform Safe & FME FME Realize Experience data in real world context, in real time.
- 16. With 500+ supporteddata types in FME. Unrivalled Data Support GIS CAD Database XML Raster 3D BIM Web Point Cloud Cloud Big Data IOT Graph BI Indoor Mapping AR/VR Generative AI Cloud Native Tabular
- 17. All Data. AnyAI. All Data Velocities Batch (ETL, Reverse ETL, ...) Event ( BPA, RPA, ...) Stream All Data Locations Any Cloud On-premises Hybrid Edge Containers Embedded Mixed All Data Types Unstructured Structured Spatial APIs Web Apps … Any AI Technology OpenAI Amazon Bedrock Google Gemini Ollama Deepseek Composite
- 18. ● ArcGIS FeatureServices ○ ArcGIS Online, Enterprise (Portal), Server ● File Geodatabase ● Shapefile ● ArcSDE Esri Integrations
- 19. ● Esri ArcGISConnector Package ○ ArcGISOnlineConnector ○ ArcGISAttachmentConnector ○ ArcGISBranchVersionManager Esri Integrations
- 20. ● Snowflake Reader& Writer ● Bulk Insert capability for large data loads ● Leverage Snowflake SQL statements ● Authentication ○ Basic ○ OAuth ○ Browser-based SSO ○ Keypair Snowflake Integrations
- 21.
- 22. Why Synchronization Matters ●Orgs are shifting to cloud platforms to take advantage of their scalability & performance ● Migration isn’t just a one-time job - ongoing synchronization is essential ● Both Esri & Snowflake play vital roles ○ Esri: spatial intelligence, visualization, field operations ○ Snowflake: scalable cloud analytics and storage
- 23. The Challenge ● Bulktransfers between Esri and Snowflake are not straightforward ○ Esri datasets often come with geometry, schema quirks ○ Snowflake excels at raw scale but can’t natively import data from Esri formats ● Organizations need a way to move data reliably and repeatedly, at scale
- 24.
- 25. ● Use theChangeDetector to easily perform CDC within FME ● Use Bulk Mode if possible ● Deploy FME close to the data ● Next Steps? ○ Automate with FME Flow using schedules or webhook triggers Outcomes
- 26.
- 27. The Challenge ● Snowflakeexcels at storing and analyzing massive spatial datasets ● It’s not built as a cartography tool / geospatial dashboards ● Esri provides rich visualization tools such as ArcGIS Online dashboards that we can leverage to display our data
- 28. Key Components ● FMEmigrates data from Snowflake to Esri in the correct schema ● Optimize queries - only send the data that’s needed for visualization ● Automate updates with FME Flow schedules to keep dashboards live
- 29. Slide Title Organizations want tovisualize their Snowflake spatial data Goal Block Key Visualizing Snowflake Spatial Data Result Snowflake dashboards can’t currently visualize spatial data Connect Snowflake to Esri and query for only the data required Businesses can now observe spatial data & analytics in a live dashboard
- 30.
- 31. ● Snowflake spatialdata is easily visualized in a live AGOL dashboard Outcomes
- 32.
- 33. The Challenge ● Business-criticaldata often comes in documents, images, and attachments ● ArcGIS supports attachments across various systems, however moving them into other systems is difficult ● Snowflake excels at structured + semi structured data, but attachments are tough to manage ● Examples ○ Field inspections: photos collected in the field ○ Engineering & planning documents stored alongside spatial records
- 34. Key Components ● ArcGISAttachmentConnector ○ Easily manage attachments in ArcGIS Online & ArcGIS Portal ○ Actions: Add, Delete, Download, List, Update ● Snowflake Stage ○ Storage location in Snowflake for our documents ○ Upload is done using a SQLExecutor
- 35. Slide Title Migrate attachments from ArcGIS Onlineto Snowflake Stage Goal Block Key Migrating Documents from Esri to Snowflake Result Manually downloading and migrating these attachments is time consuming ArcGISAttachment Connector & Snowflake Stages Automated attachment migration & tracking from Esri to Snowflake
- 36.
- 37. ● ArcGISAttachmentConnector ○ Powerfultool for listing attachment details and downloading files ● SQLExecutor ○ Easily leverage SQL queries just as you would in Snowflake ● Keep attachments traceable - update Snowflake table with attachment ID ● [Optional] TempPathNameCreator ○ Create temporary folder that FME will clean up after data is loaded Recap
- 38.
- 39. Types of SQLIntegration in a Workflow ● Snowflake Reader with WHERE clause ● Snowflake Reader/Writer with SQL To Run Before/After ● SQLExecutor & FeatureReader for mid-workflow queries ● DatabaseQuerier & SQLCreator for workflow-initiator queries
- 40. Why Pushdown Matters (AKA“Let the Database do the Work”) ● Pushdown = run filters directly in Snowflake ● Avoids loading full tables into FME ● Returns only the rows you need ● Improves speed and reduces cost ● Works with spatial filters (e.g. ST_DWithin) SNOWFLAKE SNOWFLAKE FME FME Full table Filtered data Processing Processing No Pushdown With Pushdown
- 41. SQLExecutor for Mid-Workflow Joins ●Ideal for advanced filtering and summarizing ● Accepts dynamic input (e.g. list of customer IDs) ● Executes full SQL joins and groupings
- 42. H3 Spatial Aggregation ●Uses Snowflake's built-in H3 functions ● Group points into hex cells for faster mapping ● Aggregate values by location (e.g. count, spend) ● Run spatial logic at scale, inside Snowflake ● Simplifies high-volume spatial data for visualization SELECT H3_FROMGEOGPOINT(customer_location, 7) AS h3_index, COUNT(*) AS customer_count FROM customers GROUP BY h3_index;
- 43. Slide Title Use Esribuffer geometry to analyze Snowflake customer behavior Goal Block Key Filtering and Aggregating Snowflake Data by Esri Catchments Result Snowflake data is non-spatial; Esri can’t push SQL filters into the database Use FME to pass Esri geometry into Snowflake SQL for in-database filtering and aggregation. Efficient, spatially scoped customer insights with minimal data movement
- 44.
- 45. ● Spatial filteringwith SQL reduces data volume ● SQLExecutor aggregates and enriches attributes ● FME joins Snowflake data to Esri context mid-workflow ● Optional H3 binning supports scalable spatial aggregation ● Snowflake’s built-in AI (Cortex) can generate and refine statements directly in-database ● Minimal movement, maximum insight Lessons Learned
- 46.
- 47. Summary ● FME bridgesEsri & Snowflake using flexible, spatially aware SQL workflows ● SQL logic is placed strategically to reduce load & improve performance ● Spatial joins, aggregations, H3 binning work seamlessly across systems ● FME automates these pipelines for reliable, repeatable analytics ● The result? Actionable, map-ready insights: without moving massive data
- 48. 30+ 30K+ 128 140+ 25K+ years of solvingdata challenges FME Community members countries with FME customers organizations worldwide global partners with FME services 200K+ users worldwide 200K+ users worldwide
- 49.
- 50. Resources ● Working withEsri ArcGIS Feature Services in FME ● How to Use the ArcGISAttachmentConnector ● Using FME and the Snowflake Database Format
- 51. Get our Ebook SpatialData for the Enterprise fme.ly/gzc Guided learning experiences at your fingertips academy.safe.com FME Academy Resources Check out how-to’s & demos in the knowledge base support.safe.com Knowledge Base Webinars Upcoming & on-demand webinars safe.com/webinars
- 52.
- 53. We’d love tohelp you get started. Get in touch with us at info@safe.com Experience the FME Accelerator Contact Us A world where data is not just a commodity but a catalyst for real change. fme.safe.com/accelerator Next Steps
- 54. ClaimYour Community Badge& Dive into the new Community! ● Get community badges for watching webinars ● community.safe.com ● Today’s code: MK43C5 Join the Community today! Next Steps
- 55.
- 56. ThankYou Recap of NextSteps 1 Follow us on LinkedIn! 2 Contact us 3 Experience the FME Accelerator Please fill out our webinar survey