How to Migrate from BigQuery to Snowflake

How do I plan a BigQuery → Snowflake migration?

List every dataset, table, view, and scheduled query in BigQuery. Tag owners, data size, and refresh cadence. Map each object to a Snowflake database, schema, role, and warehouse. This inventory drives later automation scripts.

What are the end-to-end steps?

1) Export BigQuery tables to Google Cloud Storage (GCS). 2) Set up an external stage in Snowflake that points to the GCS bucket. 3) Create target tables in Snowflake. 4) COPY data in. 5) Re-create views, jobs, and permissions. 6) Validate row counts and checksums.

How do I export BigQuery data to GCS?

Use the EXPORT DATA statement or the bq extract CLI. Partition large tables to avoid >1 GB file limits and enable compression for faster transfer.

What is the Snowflake loading syntax?

Snowflake loads GCS files through CREATE STAGE and COPY INTO. Key options: FILE_FORMAT, ON_ERROR, MATCH_BY_COLUMN_NAME, FORCE, and PURGE. Set MATCH_BY_COLUMN_NAME = CASE_INSENSITIVE to tolerate column order changes.

How can I migrate an ecommerce Orders table?

The example below exports Orders from BigQuery, defines a Snowflake stage, and copies data into the Snowflake ORDERS table.

Step 1 – BigQuery export

EXPORT DATA
OPTIONS (
uri='gs://bq_to_sf/orders/*.parquet',
format='PARQUET',
compression='SNAPPY')
AS
SELECT * FROM `ecom.Orders`;


Step 2 – Create stage in Snowflake

CREATE STAGE gcs_orders_stage
url='gcs://bq_to_sf/orders/'
credentials=(gcs_key_id='$GCS_KEY' gcs_secret_key='$GCS_SECRET')
file_format=(type=parquet);


Step 3 – Create target table

CREATE OR REPLACE TABLE Orders (
id BIGINT,
customer_id BIGINT,
order_date DATE,
total_amount NUMBER(10,2)
);


Step 4 – Load data

COPY INTO Orders
FROM @gcs_orders_stage
MATCH_BY_COLUMN_NAME = CASE_INSENSITIVE
ON_ERROR = ABORT_STATEMENT;


What validations should I run?

Compare row counts (SELECT COUNT(*)) and hashed totals (SUM(total_amount)) between BigQuery and Snowflake. Automate checks in CI pipelines to catch truncation or type mismatches early.

Best practices for large migrations

• Parallelize exports with partition decorators. • Compress files (Parquet or GZIP CSV) to cut egress costs. • Use Snowflake Snowpipe or Streams + Tasks for continuous loads. • Migrate views after base tables so dependencies resolve.