Question 1

What can Polytomic sync from Plain into Snowflake?

Accepted Answer

A fixed set of Plain objects rather than a discovered list. Core records are customers, companies, tenants, threads, users, tiers and label types. Conversation detail comes through as messages, notes, message attachments, message components, thread links, thread timeline events and thread discussions. There is no object called tickets: in Plain the ticket-like record is a thread, and that is the table most teams build their Snowflake models on.

Question 2

How does incremental syncing from Plain work?

Accepted Answer

Threads are read using Plain's own updated timestamp filter rather than a change feed. Each run sets its checkpoint ten minutes behind the sync start so nothing is lost to clock skew, then requests threads updated after that point, and child records are fetched for the parent threads that changed. Threads, customers, companies, tenants and several reports support this; the remaining objects are read in full each run. Because the watermark deliberately rewinds, let the sync upsert on the primary key rather than appending.

Question 3

How do Plain's nested structures arrive in Snowflake?

Accepted Answer

As real Snowflake types. Arrays and objects become ARRAY and VARIANT, and timestamps convert from ISO 8601 into TIMESTAMP_NTZ(9). Some relationships are deliberately flattened instead: thread assignee identifier, name and type, tier identifier and name, and label identifiers all arrive as ordinary columns. Two things surprise people on a first load. Plain identifiers and external identifiers are strings rather than numbers, and union type discriminators can show up as a __typename column.

Question 4

Are deleted Plain records removed from Snowflake?

Accepted Answer

Mostly no, and it is worth planning around. Plain does not expose tombstones for threads, so a deleted conversation simply stops appearing in incremental reads and the row stays in Snowflake indefinitely. Companies are the exception: Plain exposes deletion flags on them, so those come through marked. If your reporting depends on exact parity, schedule a periodic full resync of the affected tables rather than assuming incremental ETL keeps the copy aligned.

Connect Plain with Snowflake

Connect Plain and Snowflake with Polytomic

Nested values land as VARIANT

Plain's reports become tables

Threads resume where they stopped

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