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 CSV File 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 CSV File

A CSV (Comma Separated Values) file is a type of plain text file that stores tabular data in a structured format. Each line in the file represents a row of data, and each value within a row is separated by a comma. CSV files are commonly used for exchanging data between different software applications, such as spreadsheets and databases. They are also used for importing and exporting data from web applications and for data analysis. CSV files can be easily opened and edited in any text editor or spreadsheet software, making them a popular choice for data storage and transfer.

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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Methods to Move Data From CSV to DuckDB

• Method 1: Connecting CSV to DuckDB using Airbyte.
• Method 2: Connecting CSV to DuckDB manually.

Method 1: Connecting CSV to DuckDB using Airbyte

Prerequisites

1. A CSV File 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 CSV File and DuckDB, for seamless data migration.

When using Airbyte to move data from CSV File to DuckDB, it extracts data from CSV File 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 CSV File data for advanced analytics and insights within DuckDB, simplifying the ETL process and saving significant time and resources.

Step 1: Set up CSV File as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "CSV File" source connector and select "Create new connection."
3. Enter a name for your connection and click "Next."
4. In the "Configuration" tab, select the CSV file you want to connect to by clicking on the "Choose File" button and selecting the file from your local machine.
5. In the "Schema" tab, you can customize the schema of your data by selecting the appropriate data types for each column.
6. In the "Credentials" tab, enter the necessary credentials to access your CSV file. This may include a username and password or other authentication details.
7. Once you have entered your credentials, click "Test Connection" to ensure that Airbyte can successfully connect to your CSV file.
8. If the connection is successful, click "Create Connection" to save your settings and start syncing your data.
9. You can monitor the progress of your sync in the "Connections" tab and view your data in the "Destinations" tab.

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 CSV File data to DuckDB

Once you've successfully connected CSV File 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 CSV File 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 CSV File 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 CSV File 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 CSV File data.

Method 2: Connecting CSV to DuckDB manually

Moving data from a CSV file to DuckDB can be accomplished using DuckDB's built-in functions for importing CSV files. Below is a step-by-step guide on how to do this without using any third-party connectors or integrations.

Step 1: Install DuckDB

If you haven't already installed DuckDB, you can do so by downloading the appropriate binary for your system from the DuckDB website or using pip if you're using Python:

```sh

pip install duckdb

```

Step 2: Start DuckDB

You can start DuckDB using the command line or within a Python script. Here's how to do it in Python:

```python

import duckdb

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# This will create an in-memory database. To persist data, replace `:memory:` with a file path.

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

```

Step 3: Create a Table in DuckDB

Before importing the CSV data, you need to create a table in DuckDB with the appropriate schema that matches the CSV file's structure.

```python

# Replace the column names and types with the ones that match your CSV file

con.execute("""

CREATE TABLE my_table (

column1 INTEGER,

column2 VARCHAR,

column3 FLOAT

)

""")

```

Step 4: Import CSV Data into DuckDB

Now you can use DuckDB's `COPY` command to import the CSV file into the table you just created.

```python

# Replace 'my_table' with your table name and 'path/to/your/file.csv' with the path to your CSV file

con.execute("""

COPY my_table FROM 'path/to/your/file.csv' WITH (HEADER TRUE, DELIMITER ',');

""")

```

Make sure that the `HEADER` and `DELIMITER` options match the format of your CSV file. If your CSV file has a header row, set `HEADER` to `TRUE`. Adjust the `DELIMITER` option if your CSV uses a different character to separate fields.

Step 5: Verify the Data Import

After importing the data, you might want to verify that the data has been imported correctly.

```python

# This will fetch the first 10 rows from the table

result = con.execute("SELECT * FROM my_table LIMIT 10").fetchall()

print(result)

```

‍Step 6: Querying Data

You can now perform SQL queries on your data in DuckDB.

```python

# Example query: Get the count of rows in the table

row_count = con.execute("SELECT COUNT(*) FROM my_table").fetchone()

print(f"Number of rows in the table: {row_count[0]}")

```

Step 7: Save and Close the Connection

If you created a persistent database (not in-memory), you might want to commit changes and close the connection:

```python

# Commit changes if necessary (DuckDB usually auto-commits)

# con.commit()

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# Close the connection when done

con.close()

```

Additional Notes

- If your CSV file is very large, you might want to consider using the `COPY` command within DuckDB's CLI for better performance.

- Ensure that the data types in the `CREATE TABLE` statement match the corresponding fields in the CSV file to prevent data import errors.

- If your CSV contains special characters or different encodings, you may need to specify additional options in the `COPY` command to handle these correctly.

By following these steps, you should be able to move data from a CSV file into DuckDB without any third-party connectors or integrations, using DuckDB's own capabilities to handle CSV files.

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Use Cases to transfer your CSV File data to DuckDB

Integrating data from CSV File 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 CSV File data, extracting insights that wouldn't be possible within CSV File alone.
2. Data Consolidation: If you're using multiple other sources along with CSV File, 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: CSV File 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 CSV File 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 CSV File data.
6. Data Science and Machine Learning: By having CSV File data in DuckDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While CSV File 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 CSV File 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 CSV File 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 CSV File 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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