Question 1

What is this pairing used for?

Accepted Answer

It covers a range of cases, and they mostly share a shape: something needs a result computed in the lakehouse but cannot query the lakehouse itself. That might be an internal tool, a service reading account state, a customer facing view, or a downstream job that expects a relational table. Landing the modelled output in Postgres puts it where those systems already look, refreshed on whatever schedule suits, rather than through an export somebody maintains.

Question 2

How does incremental reading work?

Accepted Answer

Through a tracking column, whose last value is stored so later runs read rows past it, ordered by that column. The first run reads in full. A primary key is not required for this, though a unique key helps the reader chunk efficiently where many rows share the same tracking value. Reads of this kind will not observe deletes, since a removed row simply stops appearing rather than being flagged.

Question 3

Can Polytomic read the Delta change data feed?

Accepted Answer

No, and this is worth clearing up because the connector does mention change data feed elsewhere. That option is destination side: it sets the change data feed property on tables Polytomic creates, so your own downstream jobs can consume it. There is no reader that consumes a change data feed as a source. Source reads are full scans or incremental reads on tracking columns, which is why deletes do not propagate through them.

Question 4

How does the write into Postgres behave?

Accepted Answer

Model syncs write directly with no staging table, batching inserts and issuing updates per row, and a failed batch is retried individually so errors point at specific records. Bulk table replication stages into a scratch table and merges instead, so readers never see a partially written result. Modes are create, update, update or create, and replace, where replace clears the whole target table rather than removing only rows absent from your query.

Question 5

How do I connect Databricks to PostgreSQL?

Accepted Answer

Connect Databricks with a SQL warehouse hostname and a token, or an OAuth service principal, and connect PostgreSQL with host, port, database and credentials. Then build a model over a table or an arbitrary SQL query, map its fields onto the destination table, choose a write mode and identity field, and set a schedule. The destination table is created if it does not already exist, so no schema needs preparing first.

Connect Databricks with PostgreSQL

Connect Databricks and PostgreSQL with Polytomic

No primary key required

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Connect PostgreSQL in Polytomic

Create a sync between Databricks and PostgreSQL

Map fields and enable the sync

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