How to load data from Dremio to DuckDB

Learn how to use Airbyte to synchronize your Dremio data into DuckDB within minutes.

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Set up a Dremio connector in Airbyte

Connect to Dremio or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up DuckDB for your extracted Dremio data

Select DuckDB where you want to import data from your Dremio source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Dremio to DuckDB in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Dremio as a source connector (using Auth, or usually an API key)
set up DuckDB as a destination connector
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 Dremio

Dremio is a data-as-a-service platform that enables businesses to access and analyze their data faster and more efficiently. It provides a self-service data platform that connects to various data sources, including cloud storage, databases, and data lakes, and allows users to query and analyze data using familiar tools like SQL and BI tools. Dremio's unique approach to data processing, called Data Reflections, accelerates query performance by automatically creating optimized copies of data in memory. This allows users to get insights from their data in real-time, without the need for complex data pipelines or data warehousing. Dremio also provides enterprise-grade security and governance features to ensure data privacy and compliance.

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.

Integrate Dremio with DuckDB in minutes

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Prerequisites

A Dremio account to transfer your customer data automatically from.
A DuckDB account.
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 Dremio and DuckDB, for seamless data migration.

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

Step 1: Set up Dremio as a source connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the ""Sources"" tab on the left-hand side of the screen.
3. From there, click on the ""New Source"" button in the top right corner of the screen.
4. In the search bar, type ""Dremio"" and select the Dremio source connector from the list of available connectors.
5. Next, you will need to enter your Dremio connection details, including the host, port, username, and password.
6. Once you have entered your connection details, click on the ""Test"" button to ensure that your connection is working properly.
7. If the test is successful, click on the ""Save"" button to save your Dremio source connector.
8. You can now use your Dremio source connector to connect to your Dremio data source and begin syncing your data with Airbyte.
9. To start syncing your data, click on the ""Connections"" tab on the left-hand side of the screen and create a new connection using your Dremio source connector.
10. Follow the prompts to select your desired tables and fields to sync, and then click on the ""Start Sync"" button to begin syncing your data.

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 Dremio data to DuckDB

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

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Dremio from the dropdown list of your configured sources.
Select your destination: Choose DuckDB from the dropdown list of your configured destinations.
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.
Select the data to sync: Choose the specific Dremio objects you want to import data from towards DuckDB. You can sync all data or select specific tables and fields.
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.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Dremio 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 Dremio data.

Use Cases to transfer your Dremio data to DuckDB

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

Advanced Analytics: DuckDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Dremio data, extracting insights that wouldn't be possible within Dremio alone.
Data Consolidation: If you're using multiple other sources along with Dremio, 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.
Historical Data Analysis: Dremio has limits on historical data. Syncing data to DuckDB allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: DuckDB provides robust data security features. Syncing Dremio data to DuckDB ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: DuckDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Dremio data.
Data Science and Machine Learning: By having Dremio data in DuckDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Dremio 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 Dremio 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:

Configure a Dremio account as an Airbyte data source connector.
Configure DuckDB as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Dremio 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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How to Sync Dremio to DuckDB Manually

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Dremio?

What data can you extract from Dremio?

Dremio's API provides access to a wide range of data types, including:

1. Structured data: This includes data that is organized into tables with defined columns and rows, such as data from relational databases.

2. Semi-structured data: This includes data that has some structure, but is not organized into tables, such as JSON or XML data.

3. Unstructured data: This includes data that has no predefined structure, such as text documents, images, and videos.

4. Big data: This includes large volumes of data that cannot be processed using traditional data processing tools, such as Hadoop and Spark.

5. Streaming data: This includes real-time data that is generated continuously, such as data from IoT devices or social media feeds.

6. Cloud data: This includes data that is stored in cloud-based services, such as Amazon S3 or Microsoft Azure.

Overall, Dremio's API provides access to a wide range of data types, making it a powerful tool for data integration and analysis.

How do I transfer data from Dremio?

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 Dremio to DuckDB as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Dremio to DuckDB and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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Databases

Warehouses and Lakes

How to load data from Dremio to DuckDB

Learn how to use Airbyte to synchronize your Dremio data into DuckDB within minutes.

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Step 3: Setup a connection Use Cases Wrapping Up

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Sync data between Dremio and DuckDB

Get your data syncing in minutes

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TL;DR

set up Dremio as a source connector (using Auth, or usually an API key)
set up DuckDB as a destination connector
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 Dremio