product

Moving Data from Postgres to MotherDuck

Herman Schaaf

Herman Schaaf Jun 22, 2023

MotherDuck is a serverless analytics service powered by DuckDB. If you have data in a Postgres database that you'd like to analyze using MotherDuck, this tutorial will show you how to do this using CloudQuery, an open source ELT framework. We will cover:
  1. How to copy a Postgres database into MotherDuck as a one-off batch operation, and
  2. How to continuously stream Postgres data from Postgres to MotherDuck using Postgres Change Data Capture (CDC).
Which option you choose is up to you. Either way, by the end of this tutorial you will be able to analyze data from your Postgres database using MotherDuck.
video

Step 0. Create a Test Table in Postgres (Optional)

To demonstrate the steps in this tutorial, we will create a basic customers table in Postgres and insert 10,000 generated rows:
select
  md5(random()::text) as id,
  'person' || num || '@' ||
  (case (random() * 2)::integer
    when 0 then 'gmail'
    when 1 then 'hotmail'
    when 2 then 'yahoo'
  end) || '.com' as email,
  now() as created_at
into customers
from generate_series(1,10000) as num;
alter table customers add primary key (id);
And let's test it out:
select * from customers limit 3;
+----------------------------------+---------------------+------------------------------+
| id                               | email               | created_at                   |
|----------------------------------+---------------------+------------------------------|
| 216016a4c29d66dd007cd1c9fa9994b4 | person1@hotmail.com | 2023-06-05 14:04:38.15548+01 |
| de75a87f5f797248fd47ffcb15b7fff1 | person2@yahoo.com   | 2023-06-05 14:04:38.15548+01 |
| 279838446e9890b00e92221f25bb0c73 | person3@gmail.com   | 2023-06-05 14:04:38.15548+01 |
+----------------------------------+---------------------+------------------------------+
SELECT 3

Step 1. Install CloudQuery

CloudQuery is a cross-platform command-line tool for extracting and loading data that can be run just about anywhere: locally, on a virtual machine, or in a containerized environment. In this tutorial we'll try it out locally, and we'll use it to copy data from a local Postgres database to MotherDuck. On MacOS, you can install it using Homebrew:
brew install cloudquery/tap/cloudquery
See the CloudQuery Quickstart guide for installation instructions on other platforms. Please note that the DuckDB plugin (that we will use later) does not support Windows at this time.
Once CloudQuery is installed, you should be able to invoke it from the command line:
$ cloudquery --version
cloudquery version VERSION_CLI

Step 2. Create the Configuration File

The CloudQuery CLI is configured using YAML files. Let's create a new file called postgres-to-motherduck.yml and add the following content:
kind: source
spec:
  name: "postgresql"
  path: "cloudquery/postgresql"
  registry: "cloudquery"
  version: "VERSION_SOURCE_POSTGRESQL"
  destinations: ["motherduck"]
  tables: ["customers"]
  spec:
    connection_string: "postgresql://postgres:pass@localhost:5432/cloudquery?sslmode=disable"
---
kind: destination
spec:
  name: "motherduck"
  version: "VERSION_DESTINATION_DUCKDB"
  registry: "cloudquery"
  path: "cloudquery/duckdb"
  write_mode: "overwrite-delete-stale"
  migrate_mode: "safe"
  spec:
    connection_string: "md:"
A typical CloudQuery configuration consists of two parts: a source and a destination. A Postgres database is the source in this case, and we've configured it to copy the customers table from a locally running Postgres database. The destination is the DuckDB plugin, and instead of a local file we've configured it to write to the main MotherDuck database. You can also use an alias for the MotherDuck database, such as md:cloudquery.

Step 3. Set Up Authentication

To authenticate with MotherDuck, we need to export our service token as an environment variable. As documented in the MotherDuck documentation, you can find the token by navigating to https://app.motherduck.com/ and clicking the cog in the top right-hand corner:
Where to find your token on the MotherDuck app page
Copy the token to your clipboard and then export it as an environment variable called motherduck_token:
export motherduck_token=<INSERT YOUR TOKEN HERE>
You may also choose to place the token in your .bashrc or .zshrc file so that it is automatically loaded when you open a new terminal window. If you do this, remember to run source ~/.bashrc or source ~/.zshrc to reload your shell before continuing.

Step 4. Run a Sync

The last step is to start the sync. This will automatically create new tables in MotherDuck and start loading data from Postgres to MotherDuck.

Option 1: Run a One-Off Sync

In your terminal, run:
cloudquery sync postgres-to-motherduck.yml
This will load the rows from Postgres into MotherDuck, and exit once all the data has been copied. You should see output similar to the following:
Sync in progress

Option 2: Run a Continuous Sync with Change Data Capture (CDC)

To continuously load changes from Postgres to MotherDuck in a streaming fashion, we can add the cdc: true option to the source configuration:
kind: source
spec:
  name: "postgresql"
  path: "cloudquery/postgresql"
  registry: "cloudquery"
  version: "VERSION_SOURCE_POSTGRESQL"
  destinations: ["motherduck"]
  tables: ["customers"]
  spec:
    cdc: true  # <- This enables Change Data Capture mode
    connection_string: "postgresql://postgres:pass@localhost:5432/cloudquery?sslmode=disable"
---
kind: destination
spec:
  name: "motherduck"
  path: "cloudquery/duckdb"
  registry: "cloudquery"
  version: "VERSION_DESTINATION_DUCKDB"
  write_mode: "overwrite-delete-stale"
  migrate_mode: "safe"
  spec:
    connection_string: "md:cloudquery"
Now, back in the terminal, let's start a sync again:
cloudquery sync postgres-to-motherduck-cdc.yml
This time the sync will run continuously, and any changes made to the Postgres database will be automatically copied to MotherDuck.
CDC

Next Steps

In this post we covered how to sync both once-off and continuously from Postgres to MotherDuck from your local machine, using CloudQuery. Since your local machine won't always be available, the next step is to schedule the sync and get it production-ready. For more information about this, head over to the CloudQuery Deployment Documentation. Or if you have any questions, we're also always happy to help on Discord. Happy syncing! 🦆
Subscribe to product updates

Be the first to know about new features.