For each Kafka topic, what objects does the Snowflake Kafka Connector create?

• A. One internal stage to temporarily store data files for each topic.
• B. One pipe to ingest the data files for each topic partition.
• C. One table for each topic. If the table specified for each topic does not exist, the connector creates it; otherwise, the connector creates the RECORD_CONTENT and RECORD_METADATA columns in the existing table and verifies that the other columns are nullable (and produces an error if they are not).
• D. All of the above

Answer: (D)

The thing this question tests is how the Snowflake Kafka Connector wires each Kafka topic into Snowflake. For every topic, it creates three Snowflake artifacts that work together to load and store the data: an internal stage to hold the data files, a load pipe that ingests those files into Snowflake, and a destination table where the data ends up. The connector creates the table on first use if it doesn’t exist, and it adds the RECORD_CONTENT column for the message payload and a RECORD_METADATA column for Kafka-provided metadata (like topic, partition, offset, and timestamp). If you already have a table, the connector will append those two columns and require any existing columns to be nullable; otherwise it will raise an error to avoid schema conflicts during loads. This combination—per-topic stage, per-topic pipe, and per-topic table with content and metadata columns—is why all of the above applies. For a topic with multiple partitions, the staged files from those partitions are loaded by the per-topic pipe into the topic’s table, preserving the correlation with Kafka data through the metadata.