ARA-C01 · Question #23
A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the…
The correct answer is B. A pipe. Snowpipe (a pipe) is the most cost-effective solution for continuously ingesting large numbers of small files arriving at high frequency. Snowpipe is event-driven: it automatically triggers ingestion as new files land in the stage, avoiding the overhead and latency of scheduled…
Question
A company is storing large numbers of small JSON files (ranging from 1-4 bytes) that are received from IoT devices and sent to a cloud provider. In any given hour, 100,000 files are added to the cloud provider. What is the MOST cost-effective way to bring this data into a Snowflake table?
Options
- AAn external table
- BA pipe
- CA stream
- DA copy command at regular intervals
How the community answered
(20 responses)- B85% (17)
- C10% (2)
- D5% (1)
Explanation
Snowpipe (a pipe) is the most cost-effective solution for continuously ingesting large numbers of small files arriving at high frequency. Snowpipe is event-driven: it automatically triggers ingestion as new files land in the stage, avoiding the overhead and latency of scheduled COPY commands. For 100,000 tiny files per hour, periodic COPY commands (option D) would waste warehouse credits spinning up compute for frequent small loads. An external table (A) would query files in place but not load them efficiently. A stream (C) tracks changes in existing Snowflake tables/views, not raw files from external sources. Snowpipe uses a serverless compute model billed per-credit of actual work, making it the right fit for high-volume, small-file IoT ingestion.
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