How to Migrate from ParadeDB to BigQuery in PostgreSQL

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How do I migrate data from ParadeDB to BigQuery?

Move data from ParadeDB (PostgreSQL) to Google BigQuery safely and efficiently.

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Description

Example H2

Example H3

Why migrate from ParadeDB to BigQuery?

BigQuery offers near-infinite scale, serverless pricing, and tight GCP integration. Off-loading analytics workloads can cut ParadeDB storage costs and speed up queries.

What are the migration steps?

1. Export ParadeDB tables to CSV

Use COPY or psql \copy to stream each table to local files or Cloud Storage. CSV works best for wide compatibility.

2. Prepare schema for BigQuery

Translate PostgreSQL types to BigQuery types. VARCHAR → STRING, TIMESTAMP WITH TIME ZONE → TIMESTAMP, NUMERIC → NUMERIC. Create matching datasets and tables in BigQuery.

3. Load data into BigQuery

Run bq load or the BigQuery UI. Point to the exported CSV in Cloud Storage and supply the schema JSON or autodetect.

4. Verify data integrity

Compare row counts (SELECT COUNT(*)) and checksums on critical columns to ensure parity.

How do I automate the migration with SQL?

Wrap COPY commands in a Bash script, then call bq load per file. Use Cloud Build or GitHub Actions for repeatable CI/CD.

Best practices for ParadeDB→BigQuery migration

Export during low-traffic windows, compress CSVs with gzip, and enable BigQuery table partitioning on order_date or similar high-cardinality columns.

Common pitfalls to avoid

Avoid mismatched encodings—always set ENCODING 'UTF8'. Don’t forget to cast epoch integers to TIMESTAMP before loading.

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

How to Migrate from ParadeDB to BigQuery in PostgreSQL Example Usage


-- Verify row counts match after load
SELECT (SELECT COUNT(*) FROM Orders) AS parade_count,
       (SELECT COUNT(*) FROM `analytics.Orders`) AS bq_count;

How to Migrate from ParadeDB to BigQuery in PostgreSQL Syntax


-- Export Orders table from ParadeDB to Cloud Storage
COPY Orders TO PROGRAM 'gzip > gs://my-bucket/Orders.csv.gz' WITH (
    FORMAT csv,
    HEADER true,
    ENCODING 'UTF8'
);

-- BigQuery CLI load for Orders
bq load --source_format=CSV \
        --skip_leading_rows=1 \
        --field_delimiter="," \
        analytics.Orders \
        gs://my-bucket/Orders.csv.gz \
        id:INT64,customer_id:INT64,order_date:DATE,total_amount:NUMERIC

Common Mistakes

Ignoring timezone conversion: ParadeDB’s TIMESTAMP WITH TIME ZONE becomes UTC TIMESTAMP in BigQuery. Fix by casting to UTC during export or specifying the time zone in schema.
Loading huge files without splits: A single multi-GB CSV slows bq load. Split files (e.g., <code>split -b 1G</code>) so BigQuery can parallel-import.