How to load data from Dremio to Apache Iceberg

Learn how to use Airbyte to synchronize your Dremio data into Apache Iceberg 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 Apache Iceberg for your extracted Dremio data

Select Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg

For huge analytical tables, Apache Iceberg is a high-performance format. Using Apache Iceberg, engines such as Spark, Trino, Flink, Presto, Hive and Impala can safely work with the same tables, at the same time, providing the reliability and simplicity of SQL tables to big data. With Apache Iceberg, you can merge new data, update existing rows, and delete specific rows. Data files can be eagerly rewritten or deleted deltas can be used to make updates faster.

Integrate Dremio with Apache Iceberg in minutes

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Prerequisites

A Dremio account to transfer your customer data automatically from.
A Apache Iceberg 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 Apache Iceberg, for seamless data migration.

When using Airbyte to move data from Dremio to Apache Iceberg, it extracts data from Dremio using the source connector, converts it into a format Apache Iceberg can ingest using the provided schema, and then loads it into Apache Iceberg via the destination connector. This allows businesses to leverage their Dremio data for advanced analytics and insights within Apache Iceberg, 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 Apache Iceberg 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 "Apache Iceberg" destination connector and select "Create new connection."
3. Enter a name for your connection and provide the necessary credentials for your Apache Iceberg database, including the host, port, database name, username, and password.
4. Test the connection to ensure that it is successful. 5. Select the tables or data sources that you want to replicate to your Apache Iceberg database.
6. Configure any additional settings or options for your connection, such as the frequency of data replication or any transformations that you want to apply to your data.
7. Save your connection and start the replication process.
8. Monitor the progress of your data replication and troubleshoot any issues that may arise.
9. Once the replication process is complete, verify that your data has been successfully replicated to your Apache Iceberg database.
10. Use your Apache Iceberg database to analyze and query your data as needed.

Step 3: Set up a connection to sync your Dremio data to Apache Iceberg

Once you've successfully connected Dremio as a data source and Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg. 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 Apache Iceberg according to your settings.

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

Use Cases to transfer your Dremio data to Apache Iceberg

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

Advanced Analytics: Apache Iceberg’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 Apache Iceberg 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 Apache Iceberg allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Apache Iceberg provides robust data security features. Syncing Dremio data to Apache Iceberg ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Apache Iceberg 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 Apache Iceberg, 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 Apache Iceberg, providing more advanced business intelligence options. If you have a Dremio table that needs to be converted to a Apache Iceberg 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 Apache Iceberg as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Dremio to Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg

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

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Deploy Airbyte Open Source

TL;DR

What is Dremio

What is Apache Iceberg

Prerequisites

Step 1: Setup Dremio

Step 2: Setup Apache Iceberg

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Dremio and Apache Iceberg

Get your data syncing in minutes

Try Airbyte free

TL;DR

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

What is Apache Iceberg

Integrate Dremio with Apache Iceberg in minutes

Try for free now

Prerequisites

A Dremio account to transfer your customer data automatically from.
A Apache Iceberg 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.

Step 1: Set up Dremio as a source connector

Step 2: Set up Apache Iceberg as a destination connector

Step 3: Set up a connection to sync your Dremio data to Apache Iceberg

Once you've successfully connected Dremio as a data source and Apache Iceberg 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 Apache Iceberg 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 Apache Iceberg. 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 Apache Iceberg according to your settings.

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

Use Cases to transfer your Dremio data to Apache Iceberg

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

Advanced Analytics: Apache Iceberg’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 Apache Iceberg 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 Apache Iceberg allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Apache Iceberg provides robust data security features. Syncing Dremio data to Apache Iceberg ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Apache Iceberg 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 Apache Iceberg, 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 Apache Iceberg, providing more advanced business intelligence options. If you have a Dremio table that needs to be converted to a Apache Iceberg table, Airbyte can do that automatically.