2 posts tagged with "Change Tracking"

Migrating SQL Server to Amazon Redshift is not a backup-and-restore job. SQL Server is an operational database; Redshift is an analytical warehouse. The safest approach is to move table data continuously, validate it while SQL Server stays live, and switch downstream analytics only after the Redshift copy passes your checks.

This guide shows how to build that migration with Supaflow's SQL Server connector and Amazon Redshift connector. You will configure Redshift as the destination, connect SQL Server as the source, run an initial load, test ongoing changes, and use a controlled cutover checklist instead of betting everything on one migration window.

Need to replicate your SQL Server tables into Snowflake? Supaflow's SQL Server connector supports two query modes: Standard for simple cursor-based sync, and Change Tracking for capturing every insert, update, and delete -- including hard deletes that standard mode can never detect.

This guide walks through setting up a SQL Server to Snowflake pipeline with Change Tracking enabled, so your Snowflake tables stay in sync with every change made in SQL Server.