Official Snowflake documentation covering the full suite of data loading methods for Snowflake tables.
Bulk Loading (COPY INTO): Two-step process — upload files to a Snowflake stage using PUT, then execute COPY INTO <table>. Supports external stages (Amazon S3, Google Cloud Storage, Microsoft Azure) and Snowflake internal stages (user, table, named). Relies on user-managed virtual warehouses for compute.
Continuous Loading (Snowpipe): Serverless compute approach that loads micro-batches within minutes of file arrival. Uses cloud storage event notifications to trigger automatic loading without user-managed warehouse overhead.
Snowpipe Streaming: Low-latency, row-level ingestion API for near-real-time data. Writes rows directly to Snowflake tables without staging files, enabling sub-minute latency for streaming event pipelines.
Schema Detection: INFER_SCHEMA function automatically identifies column definitions from staged semi-structured files (Parquet, Avro, ORC, JSON, CSV), reducing manual schema definition effort.
Error Handling: DML error logging allows COPY operations to continue despite row-level errors, logging failures to a separate error table for inspection without aborting the entire load.
This overview is the reorganized successor to the former /en/user-guide/data-load-bulk-load-copy URL path, which returned HTTP 404 as of mid-2026. Provides the authoritative workflow guide for Snowflake ingestion architecture, complementing the SQL command reference (docs-snowflake-com.en-sql-reference-sql-copy-into-table-2026) with ingestion method selection guidance.