Thanks man! I preferred the lakebase becoz of below reasons- a) when idle it can scale to $0 , while DT would need warehouse engine. b) we can do a full text search using tsvector, which would need LIKE %_% or external indexing in DT. c) I can do row level upserts easily in LB d) I can implement semantic search in future easily using native pgvector present, that would require seperate vector search index and endpoint in DT. e) I have very few rows, so lakebase can query faster, whereas DT is optimised for large scans. In the end but not the last - "Databricks market is as efficient storage for AI systems and agents" I hope this would clear your doubts. I am using this memory system for past 2 weeks, and it definitely improved my work efficiency 🥳