5.1 Writing to Snowflake,RedShift or BigQuery.
Writing data to these major cloud data warehouses can be done through several methods, depending on the data source, volume, and desired latency.
🡆Batch Loading: This is the most common method for large datasets.
🡆External Storage: Data is staged in cloud storage (e.g., Amazon S3 for Redshift, Google Cloud Storage for BigQuery, or internal stages for Snowflake). Bulk copy commands are then used to load the data into the warehouse tables.
🡆ETL/ELT Tools: Data integration platforms like Matillion are specifically designed to manage and execute this batch loading process .
🡆Streaming Ingestion: For real-time data, streaming ingestion methods are used.
🡆Native Streaming APIs: Google BigQuery has a streaming API, while Snowflake uses a feature called Snowpipe for continuous data loading from staged files.
🡆Managed Streaming Services: Services like Amazon Kinesis or Google Cloud Pub/Sub can capture real-time data streams and deliver them to the respective data warehouses .
🡆Direct Inserts/Updates: For small, incremental data updates, direct SQL INSERT or UPDATE statements can be used. This method is less efficient for large data volumes .