TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

1. set up Postgres as a source connector (using Auth, or usually an API key)
2. set up DuckDB as a destination connector
3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Postgres

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many webs, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What is DuckDB

DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.

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Prerequisites

1. A Postgres account to transfer your customer data automatically from.
2. A DuckDB account.
3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Postgres and DuckDB, for seamless data migration.

When using Airbyte to move data from Postgres to DuckDB, it extracts data from Postgres using the source connector, converts it into a format DuckDB can ingest using the provided schema, and then loads it into DuckDB via the destination connector. This allows businesses to leverage their Postgres data for advanced analytics and insights within DuckDB, simplifying the ETL process and saving significant time and resources.

Methods to Move Data From Postgres to duckdb

• Method 1: Connecting Postgres to duckdb using Airbyte.
• Method 2: Connecting Postgres to duckdb manually.

Method 1: Connecting Postgres to duckdb using Airbyte

Step 1: Set up Postgres as a source connector

1. Open your PostgreSQL database and create a new user with the necessary permissions to access the data you want to replicate.

2. Obtain the hostname or IP address of your PostgreSQL server and the port number it is listening on.

3. Create a new database in PostgreSQL that will be used to store the replicated data.

4. Obtain the name of the database you just created.

5. In Airbyte, navigate to the PostgreSQL source connector and click on "Create Connection".

6. Enter a name for your connection and fill in the required fields, including the hostname or IP address, port number, database name, username, and password.

7. Test the connection to ensure that Airbyte can successfully connect to your PostgreSQL database.

8. Select the tables or views you want to replicate and configure any necessary settings, such as the replication frequency and the replication method.

9. Save your configuration and start the replication process.

10. Monitor the replication process to ensure that it is running smoothly and troubleshoot any issues that arise.

Step 2: Set up DuckDB as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button located in the top right corner of the screen.
3. Scroll down the list of available destinations until you find "DuckDB" and click on it.
4. Fill in the required information for your DuckDB database, including the host, port, database name, username, and password.
5. Test the connection to ensure that the information you provided is correct and that Airbyte can successfully connect to your DuckDB database.
6. If the connection is successful, click on the "Save" button to save your DuckDB destination connector.
7. You can now use this connector to transfer data from your source connectors to your DuckDB database. Simply select the DuckDB destination connector when setting up your data integration pipelines in Airbyte.

Step 3: Set up a connection to sync your Postgres data to DuckDB

Once you've successfully connected Postgres as a data source and DuckDB as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select Postgres from the dropdown list of your configured sources.
3. Select your destination: Choose DuckDB from the dropdown list of your configured destinations.
4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
5. Select the data to sync: Choose the specific Postgres objects you want to import data from towards DuckDB. You can sync all data or select specific tables and fields.
6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Postgres to DuckDB according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your DuckDB data warehouse is always up-to-date with your Postgres data.

Method 2: Connecting Postgres to duckdb manually.

Moving data from PostgreSQL to DuckDB without using third-party connectors or integrations involves several steps, including exporting data from PostgreSQL and importing it into DuckDB. Below is a detailed step-by-step guide:

Step 1: Export Data from PostgreSQL

1.1 Access PostgreSQL

First, you need to access your PostgreSQL database using a command-line tool like `psql` or a graphical user interface such as pgAdmin.

1.2 Choose Data to Export

Decide which tables or data you want to export from PostgreSQL. You can export entire tables or a subset of data using SQL queries.

1.3 Export Data to CSV

Use the PostgreSQL `COPY` command to export the data to a CSV file. Run the following command in the `psql` tool or your preferred PostgreSQL interface:

```sql

COPY (SELECT * FROM your_table_name) TO '/path/to/your/output.csv' WITH CSV HEADER;

```

Replace `your_table_name` with the name of the table you want to export and `/path/to/your/output.csv` with the path to the CSV file you want to create.

Step 2: Prepare DuckDB Environment

2.1 Install DuckDB

If you haven't already installed DuckDB, you can download it from the official website or install it using Python:

```bash

pip install duckdb

```

2.2 Start DuckDB

Start DuckDB using the command line or by running it in a Python script:

```python

import duckdb

conn = duckdb.connect(database=':memory:', read_only=False)

```

This will start an in-memory DuckDB instance. If you want to persist the data, provide a file path instead of `':memory:'`.

Step 3: Import Data into DuckDB

3.1 Create a Table in DuckDB

Before you can import the data, you need to create a table in DuckDB with the same schema as the PostgreSQL table you exported. You can do this using the DuckDB SQL interface:

```sql

CREATE TABLE your_table_name (

    column1 datatype1,

    column2 datatype2,

    ...

);

```

Replace `your_table_name`, `column1`, `column2`, `datatype1`, `datatype2`, etc., with the appropriate table name and column definitions.

3.2 Import Data from CSV

Use the DuckDB `COPY` command to import the CSV file into the newly created table:

```sql

COPY your_table_name FROM '/path/to/your/output.csv' WITH (FORMAT 'csv', HEADER);

```

Replace `your_table_name` with the name of the DuckDB table you created and `/path/to/your/output.csv` with the path to the CSV file you exported from PostgreSQL.

Step 4: Verify Data Integrity

4.1 Check Row Counts

To ensure that all data has been transferred correctly, compare the row counts in both the PostgreSQL and DuckDB tables:

```sql

-- In PostgreSQL

SELECT COUNT(*) FROM your_table_name;

‍

-- In DuckDB

SELECT COUNT(*) FROM your_table_name;

```

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4.2 Sample Data Check

Perform a few sample data checks to verify that the data looks correct in DuckDB:

‍

```sql

SELECT * FROM your_table_name LIMIT 10;

```

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Step 5: Clean Up

5.1 Remove Temporary Files

If you no longer need the CSV file, you can delete it to free up space:

```bash

rm /path/to/your/output.csv

```

5.2 Close Connections

Close any database connections you have opened during the process:

```python

# For DuckDB

conn.close()

```

Use Cases to transfer your Postgres data to DuckDB

Integrating data from Postgres to DuckDB provides several benefits. Here are a few use cases:

1. Advanced Analytics: DuckDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Postgres data, extracting insights that wouldn't be possible within Postgres alone.
2. Data Consolidation: If you're using multiple other sources along with Postgres, syncing to DuckDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: Postgres has limits on historical data. Syncing data to DuckDB allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: DuckDB provides robust data security features. Syncing Postgres data to DuckDB ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: DuckDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Postgres data.
6. Data Science and Machine Learning: By having Postgres data in DuckDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While Postgres provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to DuckDB, providing more advanced business intelligence options. If you have a Postgres table that needs to be converted to a DuckDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a Postgres account as an Airbyte data source connector.
2. Configure DuckDB as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from Postgres to DuckDB after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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