Question 1

How does incremental reading actually work?

Accepted Answer

You nominate a column whose value only increases. The first ETL run reads the table in full and records the highest value seen. Every run after that reads only rows above that saved value and then updates the checkpoint. It is a simple mechanism, which is also why it is predictable.

Question 2

What happens if I change the tracking field later?

Accepted Answer

The saved checkpoint no longer means anything, so the next run behaves like a first run and reads the table in full before resuming incrementally against the new column. Worth scheduling deliberately on a large table rather than discovering the cost.

Question 3

Is there change data capture on Azure SQL?

Accepted Answer

Not through this connector. There is no transaction log reader and no Change Tracking integration, so full reads and tracking field reads are the two modes available. Latency is therefore a function of your schedule rather than of replication lag.

Question 4

How do Azure SQL types land in Snowflake?

Accepted Answer

Numerics keep their precision and scale, NVARCHAR columns become VARCHAR, DATETIMEOFFSET becomes a timestamp with time zone, and BIT becomes BOOLEAN. New source columns are picked up on the next schema refresh.

Question 5

Should I sync a production database directly?

Accepted Answer

Point the connection at a readable secondary or a replica if you have one. Full table reads are ordinary SELECT traffic, but they are still traffic, and a replica keeps analytics load off the database serving your application.

Sync Azure SQL to Snowflake

Sync Azure SQL to Snowflake with Polytomic

Checkpoint per table

First run reads all

No change stream

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