Best data integration tool

Best Google Cloud Spanner to Amazon Kinesis data integration tool

Need the best tool to move or migrate Google Cloud Spanner data into Amazon Kinesis? Use ingestr for the open-source copy job, then add Bruin Cloud when the pipeline needs schedules, checks, lineage, alerts, and audit trails.

Open-source CLI Incremental loads Production ready

Short answer

Use ingestr when you need a direct, scriptable Google Cloud Spanner to Amazon Kinesis move.

For a Google Cloud Spanner to Amazon Kinesis migration, start with ingestr: an open-source CLI, a repo-friendly command, and incremental loading when the source supports it. Bruin Cloud is the upgrade when the same job needs scheduling, quality checks, lineage, alerts, and audit logs.

Start with a local CLI command and commit the workflow to your repo.

Use incremental or time-based loading when the source supports it.

Verify row counts and schema expectations before scheduling.

Add Bruin Cloud for orchestration, lineage, checks, alerts, and audit logs.

What you'll learn

How to install and set up ingestr in seconds
Connect to Google Cloud Spanner and Amazon Kinesis 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
  • Google Cloud service account
  • Spanner database access
  • AWS credentials
  • Kinesis stream access 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 Google Cloud Spanner to Amazon Kinesis. This example shows a complete, working command you can adapt to your needs.

Set up your connections

Google Cloud Spanner connection format:

spanner://projects/<project>/instances/<instance>/databases/<database>?credentials_path=<credentials_path>

Parameters:

  • • project: Google Cloud project ID
  • • instance: Spanner instance ID
  • • database: Spanner database name
  • • credentials_path: Path to Google Cloud service account JSON file

Amazon Kinesis connection format:

kinesis://?access_key_id=<access_key_id>&secret_access_key=<secret_access_key>&region_name=<region_name>&stream_name=<stream_name>

Parameters:

  • • access_key_id: AWS access key ID
  • • secret_access_key: AWS secret access key
  • • region_name: AWS region for the Kinesis stream
  • • stream_name: Kinesis data stream name

Run your first copy

Copy the entire users table from Google Cloud Spanner to Amazon Kinesis:

ingestr ingest \
    --source-uri 'spanner://projects/my-project/instances/my-instance/databases/my-db?credentials_path=/path/to/creds.json' \
    --source-table 'public.users' \
    --dest-uri 'kinesis://?access_key_id=AKIABC123&secret_access_key=secret&region_name=us-east-1&stream_name=my-stream' \
    --dest-table 'raw.users'

What this does:

  • • Connects to your Google Cloud Spanner database
  • • Reads all data from the specified table
  • • Creates the table in Amazon Kinesis 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 Amazon Kinesis:

-- Run this in Amazon Kinesis
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 'spanner://projects/my-project/instances/my-instance/databases/my-db?credentials_path=/path/to/creds.json' \
    --source-table 'public.orders' \
    --dest-uri 'kinesis://?access_key_id=AKIABC123&secret_access_key=secret&region_name=us-east-1&stream_name=my-stream' \
    --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 Google Cloud Spanner to Amazon Kinesis 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 'spanner://projects/my-project/instances/my-instance/databases/my-db?credentials_path=/path/to/creds.json' \
    --source-table 'public.customers' \
    --dest-uri 'kinesis://?access_key_id=AKIABC123&secret_access_key=secret&region_name=us-east-1&stream_name=my-stream' \
    --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 'spanner://projects/my-project/instances/my-instance/databases/my-db?credentials_path=/path/to/creds.json' \
    --source-table 'public.transactions' \
    --dest-uri 'kinesis://?access_key_id=AKIABC123&secret_access_key=secret&region_name=us-east-1&stream_name=my-stream' \
    --dest-table 'warehouse.transactions_historical'

Development Environment Sync

Copy production data to your development Amazon Kinesis instance (with sensitive data excluded). 

# Copy sample data to development
ingestr ingest \
    --source-uri 'spanner://projects/my-project/instances/my-instance/databases/my-db?credentials_path=/path/to/creds.json' \
    --source-table 'public.products' \
    --dest-uri 'kinesis://?access_key_id=AKIABC123&secret_access_key=secret&region_name=us-east-1&stream_name=my-stream' \
    --dest-table 'dev.products' \
    --limit 1000  # Only copy 1000 rows for testing

Choosing a Google Cloud Spanner to Amazon Kinesis data integration tool

If you're comparing the best data integration tools to move or migrate Google Cloud Spanner data into Amazon Kinesis, ask a practical question: can the first copy run locally and stay reviewable when it becomes a production pipeline?

What is the best data integration tool to move data from Google Cloud Spanner to Amazon Kinesis?

For most teams, ingestr is the best starting point for moving or migrating Google Cloud Spanner data into Amazon Kinesis. It runs as an open-source CLI from your terminal, CI, or scheduler. Use Bruin Cloud when the same pipeline needs orchestration, lineage, monitoring, checks, and governance.

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 Google Cloud Spanner to Amazon Kinesis 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 Google Cloud Spanner to Amazon Kinesis.

Connection refused or timeout errors

Check your connection details:

Authentication failures

Common authentication issues:

Schema or data type mismatches

Handling data type differences:

  • ingestr automatically handles most type conversions
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 Google Cloud Spanner to Amazon Kinesis with ingestr. For production workloads with monitoring, scheduling, and data quality checks, explore Bruin Cloud.

Star ingestr on GitHub