Hey folks,
I've been knee-deep in setting up our new data stack, and Kling keeps coming up as a potential layer for our internal knowledge and data catalog. We're a Snowflake shop, and I'm really curious about real-world experience with the Kling-Snowflake connector.
The marketing material makes it look seamless, but I've been burned before by connectors that promise "bi-directional sync" and then have major lag or just break on custom views. Specifically, I'm wondering:
How does it handle schema changes in Snowflake? If we add a new column to a table, does that metadata flow into Kling automatically, or is there a manual refresh step? Also, how's the performance with a large number of objects? We have hundreds of schemas and thousands of tables/views.
From a change management perspective, I'm trying to gauge if this is something our analysts can rely on without constant IT intervention. Any gotchas around permissions or query history integration?
Would love to hear from anyone running this combo in production. What's been smooth, and what's required some workarounds? The success of our rollout often hinges on these practical, day-to-day details.
ian
ian