5-minute tutorial

Copy Data from PostgreSQL to ClickHouse with ingestr

Learn how to move PostgreSQL data into ClickHouse 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 PostgreSQL and ClickHouse 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
  • PostgreSQL server accessible from your network
  • Database user with appropriate permissions
  • pg_hba.conf configured to allow connections
  • Firewall rules allowing port 5432 (or custom port)
  • ClickHouse server access
  • Database credentials

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 PostgreSQL to ClickHouse. This example shows a complete, working command you can adapt to your needs.

Set up your connections

PostgreSQL connection format:

postgresql://username:password@host:port/database?sslmode=disable

Parameters:

  • • username: Database user
  • • password: User password
  • • host: Database server hostname or IP
  • • port: Server port (default 5432)
  • • database: Database name
  • • sslmode: SSL mode (disable, require, verify-ca, verify-full)

ClickHouse connection format:

clickhouse://<username>:<password>@<host>:<port>?secure=<secure>&http_port=<http_port>

Parameters:

  • • username: Username for ClickHouse authentication
  • • password: Password for ClickHouse authentication
  • • host: Hostname or IP address of ClickHouse server
  • • port: TCP port number for ClickHouse server
  • • http_port: HTTP port for ClickHouse server (default: 8443)
  • • secure: Use secure connection: 1 for HTTPS, 0 for HTTP (default: 1)

Run your first copy

Copy the entire users table from PostgreSQL to ClickHouse:

ingestr ingest \
    --source-uri 'postgresql://myuser:mypass@localhost:5432/mydb?sslmode=require' \
    --source-table 'public.users' \
    --dest-uri 'clickhouse://user_123:pass123@localhost:9000?secure=1&http_port=8443' \
    --dest-table 'raw.users'

What this does:

  • • Connects to your PostgreSQL database
  • • Reads all data from the specified table
  • • Creates the table in ClickHouse 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 ClickHouse:

-- Run this in ClickHouse
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 'postgresql://myuser:mypass@localhost:5432/mydb?sslmode=require' \
    --source-table 'public.orders' \
    --dest-uri 'clickhouse://user_123:pass123@localhost:9000?secure=1&http_port=8443' \
    --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 PostgreSQL to ClickHouse 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 'postgresql://myuser:mypass@localhost:5432/mydb?sslmode=require' \
    --source-table 'public.customers' \
    --dest-uri 'clickhouse://user_123:pass123@localhost:9000?secure=1&http_port=8443' \
    --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 'postgresql://myuser:mypass@localhost:5432/mydb?sslmode=require' \
    --source-table 'public.transactions' \
    --dest-uri 'clickhouse://user_123:pass123@localhost:9000?secure=1&http_port=8443' \
    --dest-table 'warehouse.transactions_historical'

Development Environment Sync

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

# Copy sample data to development
ingestr ingest \
    --source-uri 'postgresql://myuser:mypass@localhost:5432/mydb?sslmode=require' \
    --source-table 'public.products' \
    --dest-uri 'clickhouse://user_123:pass123@localhost:9000?secure=1&http_port=8443' \
    --dest-table 'dev.products' \
    --limit 1000  # Only copy 1000 rows for testing

Choosing a PostgreSQL to ClickHouse data integration tool

If you're comparing ways to move PostgreSQL data into ClickHouse, 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 PostgreSQL to ClickHouse?

ingestr is a good fit when you want an open-source CLI for PostgreSQL to ClickHouse 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 PostgreSQL to ClickHouse 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 PostgreSQL to ClickHouse.

Connection refused or timeout errors

Check your connection details:

  • Check pg_hba.conf for authentication settings
  • Verify listen_addresses in postgresql.conf
  • Ensure firewall allows connections on PostgreSQL port
  • Test with psql client first to isolate issues
Authentication failures

Common authentication issues:

  • Check pg_hba.conf for authentication settings
  • Verify listen_addresses in postgresql.conf
  • Ensure firewall allows connections on PostgreSQL port
  • Test with psql client first to isolate issues
Schema or data type mismatches

Handling data type differences:

  • ingestr automatically handles most type conversions
  • PostgreSQL: JSONB fields may need special handling
  • PostgreSQL: Arrays are PostgreSQL-specific feature
  • PostgreSQL: UUID type requires proper mapping
  • PostgreSQL: Custom types may need conversion
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 PostgreSQL to ClickHouse with ingestr. For production workloads with monitoring, scheduling, and data quality checks, explore Bruin Cloud.

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