snowflake-migration-deep-dive

# Snowflake Migration Deep Dive ## Overview Comprehensive guide for migrating to Snowflake from Redshift, BigQuery, on-prem databases, or other data warehouses. ## Migration Types | Source | Complexity | Duration | Key Challenge | |--------|-----------|----------|---------------| | Amazon Redshift | Medium | 2-6 weeks | SQL dialect differences | | Google BigQuery | Medium | 2-6 weeks | Nested/repeated fields | | On-prem (Oracle/SQL Server) | High | 1-3 months | Data transfer bandwidth | | Another Snowflake account | Low | Days | Replication or data sharing | ## Instructions ### Step 1: Schema Conversion ```sql -- Common SQL differences from Redshift/BigQuery -- Redshift DISTKEY/SORTKEY → Snowflake clustering (optional, for large tables) -- Redshift: CREATE TABLE orders (id INT) DISTSTYLE KEY DISTKEY(customer_id) SORTKEY(order_date); -- Snowflake: CREATE TABLE orders ( id INTEGER AUTOINCREMENT, customer_id INTEGER, order_date TIMESTAMP_NTZ ); ALTER TABLE orders CLUSTER BY (order_date); -- Only for tables > 1TB -- Redshift IDENTITY → Snowflake AUTOINCREMENT -- Redshift: id INT IDENTITY(1,1) -- Snowflake: id INTEGER AUTOINCREMENT START 1 INCREMENT 1 -- BigQuery STRUCT/ARRAY → Snowflake VARIANT/ARRAY -- BigQuery: address STRUCT<street STRING, city STRING> -- Snowflake: CREATE TABLE customers ( id INTEGER, address VARIANT -- Store as JSON: {"street": "...", "city": "..."} ); -- Access: SELECT address:street::VARCHAR FROM customers -- BigQuery REPEATED fields...