Tutorials
Moving Data from Postgres to MotherDuck
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:
- How to copy a Postgres database into MotherDuck as a one-off batch operation, and
- 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.
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 | [email protected] | 2023-06-05 14:04:38.15548+01 |
| de75a87f5f797248fd47ffcb15b7fff1 | [email protected] | 2023-06-05 14:04:38.15548+01 |
| 279838446e9890b00e92221f25bb0c73 | [email protected] | 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: 'v6.9.2'
destinations: ['motherduck']
tables: ['customers']
spec:
connection_string: 'postgresql://postgres:pass@localhost:5432/cloudquery?sslmode=disable'
---
kind: destination
spec:
name: 'motherduck'
version: 'v5.9.18'
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: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:
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: 'v6.9.2'
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: 'v5.9.18'
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.
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.
Ready to build your own cloud asset inventory? You can download and use CloudQuery and follow along with our quick start guide, or explore CloudQuery Cloud for a more scalable solution.
Want help getting started? Join the CloudQuery community to connect with other users and experts, or message our team directly here if you have any questions.
Written by Herman Schaaf
Herman is the Director of Engineering at CloudQuery and an Apache Arrow contributor. A polyglot with a preference for Go and Python, he has spoken at QCon London and Data Council New York.