How to Migrate from ParadeDB to Snowflake in PostgreSQL

How do I migrate data from ParadeDB (PostgreSQL) into Snowflake?

Move data from your ParadeDB (PostgreSQL) instance into Snowflake quickly and safely by exporting, staging, and bulk-loading tables.

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Description

What does “migrating from ParadeDB to Snowflake” mean?

You export tables from ParadeDB (a Postgres extension) into flat files, stage those files in a Snowflake external or internal stage, then run COPY INTO to recreate the tables and load the data.

Which tools are required?

Install psql or any Postgres client for the export, a cloud-storage CLI (AWS CLI, Azure CLI, or GCloud) for staging, and SnowSQL for loading and validation.

How do I export data from ParadeDB?

Using CSV with headers

Run COPY (SELECT * FROM Customers ORDER BY id) TO '/tmp/customers.csv' WITH CSV HEADER.Repeat for Orders, Products, and OrderItems.

Using compressed Parquet

For faster downstream load times, export to Parquet: COPY Customers TO PROGRAM 'gzip > /tmp/customers.parquet.gz' (FORMAT PARQUET).

How do I stage files in Snowflake?

Create a named stage: CREATE OR REPLACE STAGE ecommerce_stage FILE_FORMAT = (TYPE = CSV FIELD_OPTIONALLY_ENCLOSED_BY='"' SKIP_HEADER=1); Then upload: aws s3 cp /tmp/customers.csv s3://my-bucket/ecommerce/.

How do I load data into Snowflake tables?

Re-create the schema

Generate CREATE TABLE scripts from ParadeDB using pg_dump -s, tweak datatypes where needed (e.g., serial ➝ IDENTITY).

Bulk-load with COPY INTO

Run COPY INTO Customers FROM @ecommerce_stage/customers.csv FILE_FORMAT = (FORMAT_NAME = 'CSV_CFG') ON_ERROR = 'ABORT_STATEMENT';

How do I validate the migration?

Compare row counts: SELECT 'Customers' AS tbl, COUNT(*) FROM Customers UNION ALL SELECT 'Customers', row_count FROM snowflake.information_schema.tables WHERE table_name='CUSTOMERS';

Spot-check checksums: export MD5 hashes of key columns in both systems and compare.

What best practices ensure a smooth migration?

Load reference tables first, then fact tables with foreign keys; disable constraints during load; use Snowflake WAREHOUSE size XL for large batches; run loads in parallel.

What are common mistakes?

Forgetting to define the correct FILE_FORMAT leads to load errors; using inconsistent time zones causes timestamp drift.

How do I automate future loads?

Create a Snowflake TASK that runs a COPY INTO on a schedule, or trigger Snowpipe on new S3 object creation.

Why How to Migrate from ParadeDB to Snowflake in PostgreSQL is important

How to Migrate from ParadeDB to Snowflake in PostgreSQL Example Usage


-- Full flow for the Products table
-- 1. Export from ParadeDB
COPY Products TO '/tmp/products.csv' WITH CSV HEADER;

-- 2. Upload to S3
aws s3 cp /tmp/products.csv s3://my-bucket/ecommerce/

-- 3. Create Products table in Snowflake
CREATE OR REPLACE TABLE Products (
    id          INTEGER,
    name        STRING,
    price       NUMBER(10,2),
    stock       INTEGER
);

-- 4. Load data
COPY INTO Products FROM @ecommerce_stage/products.csv
FILE_FORMAT = (FORMAT_NAME='CSV_CFG')
ON_ERROR='CONTINUE';

How to Migrate from ParadeDB to Snowflake in PostgreSQL Syntax


-- Export from ParadeDB
COPY (SELECT * FROM Customers ORDER BY id)
TO '/tmp/customers.csv' WITH (
    FORMAT CSV,
    HEADER TRUE,
    DELIMITER ','
);

-- Create stage in Snowflake
CREATE OR REPLACE STAGE ecommerce_stage
    URL='s3://my-bucket/ecommerce/'
    CREDENTIALS = (AWS_KEY_ID='...' AWS_SECRET_KEY='...')
    FILE_FORMAT = (TYPE=CSV FIELD_OPTIONALLY_ENCLOSED_BY='"' SKIP_HEADER=1);

-- Load into Snowflake table
COPY INTO Customers (
    id, name, email, created_at
)
FROM @ecommerce_stage/customers.csv
FILE_FORMAT = (FORMAT_NAME = 'CSV_CFG')
ON_ERROR = 'ABORT_STATEMENT'
PURGE = TRUE;

-- Repeat for Orders, Products, OrderItems

Common Mistakes

Using default CSV settings. ParadeDB exports may include headers or "," inside text. Always specify HEADER and QUOTE characters, then mirror the same FILE_FORMAT in Snowflake. Otherwise COPY INTO fails.
Loading child tables before parents. Foreign-key enforcement in Snowflake will reject orphaned rows. Disable constraints or load dimension/reference tables first, then facts.