Can I run MySQL to Google Cloud Storage ingestion incrementally?

Yes. Use snapshot-plus-incremental or time-based extraction when the source supports it so the first load stays simple and later runs only move new or changed data.

5-minute tutorial

Copy Data from MySQL to Google Cloud Storage with ingestr

Learn how to move MySQL data into Google Cloud Storage with a repeatable CLI workflow using ingestr.

One command Zero code Production ready

What you'll learn

How to install and set up ingestr in seconds

Connect to MySQL and Google Cloud Storage with proper authentication

Copy entire tables or specific data with a single command

Set up incremental loading for continuous data synchronization

Prerequisites

Python 3.8 or higher installed
MySQL server running and accessible
User with appropriate GRANT permissions
Database exists or permission to create
Network access to MySQL port
Google Cloud service account
Storage Admin or appropriate bucket permissions

Step 1: Install ingestr

Install ingestr in seconds using pip. Choose the method that works best for you:

Recommended: Using uv (fastest)

# Install uv first if you haven't already
pip install uv

# Run ingestr using uvx
uvx ingestr

Alternative: Global installation

# Install globally using uv
uv pip install --system ingestr

# Or using standard pip
pip install ingestr

Verify installation: Run ingestr --version to confirm it's installed correctly.

Step 2: Your First Migration

Let's copy a table from MySQL to Google Cloud Storage. This example shows a complete, working command you can adapt to your needs.

Set up your connections

MySQL connection format:

mysql://username:password@host:port/database

Parameters:

• username: MySQL user
• password: User password
• host: Server hostname or IP
• port: Server port (default 3306)
• database: Database name
• charset: Optional character set

Google Cloud Storage connection format:

gcs://?credentials_path=<credentials_path>&project_id=<project_id>

Parameters:

• credentials_path: Path to Google Cloud service account JSON file
• project_id: Google Cloud Project ID

Run your first copy

Copy the entire users table from MySQL to Google Cloud Storage:

ingestr ingest \
    --source-uri 'mysql://root:password@localhost:3306/myapp' \
    --source-table 'users' \
    --dest-uri 'gcs://?credentials_path=/path/to/credentials.json&project_id=my-project' \
    --dest-table 'raw.users'

What this does:

• Connects to your MySQL database
• Reads all data from the specified table
• Creates the table in Google Cloud Storage if needed
• Copies all rows to the destination

Command breakdown:

--source-uri Your source database
--source-table Table to copy from
--dest-uri Your destination
--dest-table Where to write data

Step 3: Verify your data

After the migration completes, verify your data was copied correctly:

Check row count in Google Cloud Storage:

-- Run this in Google Cloud Storage
SELECT COUNT(*) as row_count 
FROM raw.users;

-- Check a sample of the data
SELECT * 
FROM raw.users 
LIMIT 10;

Advanced Patterns

Once you've mastered the basics, use these patterns for production workloads.

Only copy new or updated records since the last sync. Perfect for daily updates.

ingestr ingest \
    --source-uri 'mysql://root:password@localhost:3306/myapp' \
    --source-table 'public.orders' \
    --dest-uri 'gcs://?credentials_path=/path/to/credentials.json&project_id=my-project' \
    --dest-table 'raw.orders' \
    --incremental-strategy merge \
    --incremental-key updated_at \
    --primary-key order_id

How it works: The merge strategy updates existing rows and inserts new ones based on the primary key. Only rows where updated_at has changed will be processed.

Common Use Cases

Ready-to-use commands for typical MySQL to Google Cloud Storage scenarios.

Daily Customer Data Sync

Keep your analytics warehouse updated with the latest customer information every night.

# Add this to your cron job or scheduler
ingestr ingest \
    --source-uri 'mysql://root:password@localhost:3306/myapp' \
    --source-table 'public.customers' \
    --dest-uri 'gcs://?credentials_path=/path/to/credentials.json&project_id=my-project' \
    --dest-table 'analytics.customers' \
    --incremental-strategy merge \
    --incremental-key updated_at \
    --primary-key customer_id

Historical Data Migration

One-time migration of all historical records to your data warehouse.

# One-time full table copy
ingestr ingest \
    --source-uri 'mysql://root:password@localhost:3306/myapp' \
    --source-table 'public.transactions' \
    --dest-uri 'gcs://?credentials_path=/path/to/credentials.json&project_id=my-project' \
    --dest-table 'warehouse.transactions_historical'

Development Environment Sync

Copy production data to your development Google Cloud Storage instance (with sensitive data excluded).

# Copy sample data to development
ingestr ingest \
    --source-uri 'mysql://root:password@localhost:3306/myapp' \
    --source-table 'public.products' \
    --dest-uri 'gcs://?credentials_path=/path/to/credentials.json&project_id=dev-project' \
    --dest-table 'dev.products' \
    --limit 1000  # Only copy 1000 rows for testing

Choosing a MySQL to Google Cloud Storage data integration tool

If you're comparing ways to move MySQL data into Google Cloud Storage, start with the path you can run locally, review in code, and schedule later.

What is the best data integration tool to move data from MySQL to Google Cloud Storage?

ingestr is a good fit when you want an open-source CLI for MySQL to Google Cloud Storage ingestion. You can run it from your terminal, CI, or a scheduled job, then move the same pipeline into Bruin Cloud when you need orchestration, lineage, and monitoring.

Can this run as an incremental pipeline?

Yes. Use snapshot-plus-incremental or time-based extraction when the source supports it. That keeps the first load simple while making later runs smaller and easier to monitor.

When should I use Bruin Cloud with ingestr?

Use Bruin Cloud when the MySQL to Google Cloud Storage pipeline needs schedules, alerts, data quality checks, audit trails, or catalog and lineage visibility for the rest of the team.

Troubleshooting Guide

Solutions to common issues when migrating from MySQL to Google Cloud Storage.

Connection refused or timeout errors

Check your connection details:

Check bind-address in my.cnf (should not be 127.0.0.1 for remote)
Verify user has permission from connecting host
Ensure port 3306 is not blocked by firewall
Test with mysql client to isolate issues

Authentication failures

Common authentication issues:

Check bind-address in my.cnf (should not be 127.0.0.1 for remote)
Verify user has permission from connecting host
Ensure port 3306 is not blocked by firewall
Test with mysql client to isolate issues

Schema or data type mismatches

Handling data type differences:

ingestr automatically handles most type conversions
MySQL: JSON type available in MySQL 5.7+
MySQL: DATETIME vs TIMESTAMP timezone handling
MySQL: Character set and collation settings
MySQL: Strict mode affects data validation

Performance issues with large tables

Optimize large data transfers:

Use incremental loading to process data in chunks
Run migrations during off-peak hours
Split very large tables by date ranges using interval parameters

Ready to scale your data pipeline?

You've learned how to migrate data from MySQL to Google Cloud Storage with ingestr. For production workloads with monitoring, scheduling, and data quality checks, explore Bruin Cloud.

Star ingestr on GitHub