How to load data from n8n to Databricks Lakehouse

Learn how to use Airbyte to synchronize your n8n data into Databricks Lakehouse within minutes.

Try Airbyte Cloud
Get a demo

Trusted by data-driven companies

Building your pipeline or Using Airbyte

Airbyte is the only open solution empowering data teams  to meet all their growing custom business demands in the new AI era.

Building in-house pipelines
Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
After Airbyte
Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a n8n connector in Airbyte

Connect to n8n or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Databricks Lakehouse for your extracted n8n data

Select Databricks Lakehouse where you want to import data from your n8n source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the n8n to Databricks Lakehouse 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.
Try Airbyte Cloud

Take a virtual tour

Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

Talk to our team

Old Automated Content

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 n8n as a source connector (using Auth, or usually an API key)
  2. set up Databricks Lakehouse 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 n8n

N8n is a free and open fair-code distributed node-based Workflow Automation Tool. You can self-host n8n, easily extend it, and even you can use it. n8n is an extendable workflow automation tool that enables you to connect anything to everything via its open, fair-code model. Berlin, Germany n8n. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic, and apps.

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate n8n with Databricks Lakehouse in minutes

Try for free now

Prerequisites

  1. A n8n account to transfer your customer data automatically from.
  2. A Databricks Lakehouse 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 n8n and Databricks Lakehouse, for seamless data migration.

When using Airbyte to move data from n8n to Databricks Lakehouse, it extracts data from n8n using the source connector, converts it into a format Databricks Lakehouse can ingest using the provided schema, and then loads it into Databricks Lakehouse via the destination connector. This allows businesses to leverage their n8n data for advanced analytics and insights within Databricks Lakehouse, simplifying the ETL process and saving significant time and resources.

Step 1: Set up n8n as a source connector

1. Open the N8n workflow editor and create a new workflow.
2. Drag and drop the "HTTP Request" node onto the workflow canvas.
3. Double-click the "HTTP Request" node to open its settings.
4. In the "URL" field, enter the endpoint URL for your Airbyte source connector. This can be found in the Airbyte documentation for your specific connector.
5. In the "Headers" section, add the following key-value pairs:  - "Content-Type": "application/json"  - "Authorization": "Bearer {{YOUR_AIRBYTE_API_KEY}}"  Replace "{{YOUR_AIRBYTE_API_KEY}}" with your actual Airbyte API key.
6. In the "Query Parameters" section, add any necessary query parameters for your specific connector. Again, refer to the Airbyte documentation for your connector for more information.
7. Click "Save" to save the settings for the "HTTP Request" node.
8. Connect the "HTTP Request" node to the next node in your workflow.
9. Continue building your workflow as desired, using the data returned by the Airbyte source connector in subsequent nodes.

Step 2: Set up Databricks Lakehouse as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Databricks Lakehouse" connector and click on it.
4. You will be prompted to enter your Databricks Lakehouse credentials, including your account name, personal access token, and workspace ID.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your Databricks Lakehouse destination connector settings.
7. You can now use the Databricks Lakehouse connector to transfer data from your source connectors to your Databricks Lakehouse destination.
8. To set up a data transfer, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector credentials and configure your data transfer settings.
10. Once you have configured your source connector, select the Databricks Lakehouse connector as your destination and follow the prompts to configure your data transfer settings.
11. Click on the "Run" button to initiate the data transfer.

Step 3: Set up a connection to sync your n8n data to Databricks Lakehouse

Once you've successfully connected n8n as a data source and Databricks Lakehouse 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 n8n from the dropdown list of your configured sources.
  3. Select your destination: Choose Databricks Lakehouse 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 n8n objects you want to import data from towards Databricks Lakehouse. 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 n8n to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your n8n data.

Use Cases to transfer your n8n data to Databricks Lakehouse

Integrating data from n8n to Databricks Lakehouse provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your n8n data, extracting insights that wouldn't be possible within n8n alone.
  2. Data Consolidation: If you're using multiple other sources along with n8n, syncing to Databricks Lakehouse 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: n8n has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing n8n data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding n8n data.
  6. Data Science and Machine Learning: By having n8n data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While n8n provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a n8n table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a n8n account as an Airbyte data source connector.
  2. Configure Databricks Lakehouse as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from n8n to Databricks Lakehouse 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!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

What sets Airbyte Apart

Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

An Extensible Open-Source Standard

More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s Connector Builder lets you edit or add new connectors in minutes.

Full Control & Security

Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

Enterprise Support with SLAs

Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Jean-Mathieu Saponaro
Data & Analytics Senior Eng Manager

"The intake layer of Datadog’s self-serve analytics platform is largely built on Airbyte.Airbyte’s ease of use and extensibility allowed any team in the company to push their data into the platform - without assistance from the data team!"

Learn more
Chase Zieman headshot
Chase Zieman
Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Learn more
Alexis Weill
Data Lead

“We chose Airbyte for its ease of use, its pricing scalability and its absence of vendor lock-in. Having a lean team makes them our top criteria.
The value of being able to scale and execute at a high level by maximizing resources is immense”

Learn more

Sync with Airbyte

1. Open the N8n workflow editor and create a new workflow.
2. Drag and drop the "HTTP Request" node onto the workflow canvas.
3. Double-click the "HTTP Request" node to open its settings.
4. In the "URL" field, enter the endpoint URL for your Airbyte source connector. This can be found in the Airbyte documentation for your specific connector.
5. In the "Headers" section, add the following key-value pairs:  - "Content-Type": "application/json"  - "Authorization": "Bearer {{YOUR_AIRBYTE_API_KEY}}"  Replace "{{YOUR_AIRBYTE_API_KEY}}" with your actual Airbyte API key.
6. In the "Query Parameters" section, add any necessary query parameters for your specific connector. Again, refer to the Airbyte documentation for your connector for more information.
7. Click "Save" to save the settings for the "HTTP Request" node.
8. Connect the "HTTP Request" node to the next node in your workflow.
9. Continue building your workflow as desired, using the data returned by the Airbyte source connector in subsequent nodes.

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Databricks Lakehouse" connector and click on it.
4. You will be prompted to enter your Databricks Lakehouse credentials, including your account name, personal access token, and workspace ID.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your Databricks Lakehouse destination connector settings.
7. You can now use the Databricks Lakehouse connector to transfer data from your source connectors to your Databricks Lakehouse destination.
8. To set up a data transfer, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector credentials and configure your data transfer settings.
10. Once you have configured your source connector, select the Databricks Lakehouse connector as your destination and follow the prompts to configure your data transfer settings.
11. Click on the "Run" button to initiate the data transfer.

Once you've successfully connected n8n as a data source and Databricks Lakehouse 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 n8n from the dropdown list of your configured sources.
  3. Select your destination: Choose Databricks Lakehouse 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 n8n objects you want to import data from towards Databricks Lakehouse. 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 n8n to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your n8n data.

How to Sync n8n to Databricks Lakehouse Manually

FAQs

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.

N8n is a free and open fair-code distributed node-based Workflow Automation Tool. You can self-host n8n, easily extend it, and even you can use it. n8n is an extendable workflow automation tool that enables you to connect anything to everything via its open, fair-code model. Berlin, Germany n8n. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic, and apps.

N8n's API provides access to a wide range of data types, including:  

1. Workflow data: This includes information about the workflows created in n8n, such as their names, descriptions, and trigger events.  
2. Node data: This includes data related to the individual nodes used in workflows, such as their names, types, and configurations.  
3. Execution data: This includes information about the execution of workflows, such as the start and end times, the status of each node, and any errors encountered.  
4. Credentials data: This includes data related to the credentials used to authenticate with external services, such as API keys and access tokens.  
5. Workflow run data: This includes data related to the runs of individual workflows, such as the input and output data, the status of each node, and any errors encountered.  
6. Node run data: This includes data related to the runs of individual nodes within workflows, such as the input and output data, the status of the node, and any errors encountered.  

Overall, n8n's API provides access to a comprehensive set of data types that can be used to monitor and manage workflows, troubleshoot issues, and optimize performance.

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 N8n to Databricks Lakehouse 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 N8n to Databricks Lakehouse and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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.

Back to all tutorials
Warehouses and Lakes
Marketing Analytics

How to load data from n8n to Databricks Lakehouse

Learn how to use Airbyte to synchronize your n8n data into Databricks Lakehouse within minutes.

TL;DR
What is n8n
What is Databricks Lakehouse
Prerequisites
Step 1: Setup n8n
Step 2: Setup Databricks Lakehouse
Step 3: Setup a connectionUse CasesWrapping Up
Example H2
Example H3

Sync data between n8n and Databricks Lakehouse

Try Airbyte free

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 n8n as a source connector (using Auth, or usually an API key)
  2. set up Databricks Lakehouse 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 n8n

N8n is a free and open fair-code distributed node-based Workflow Automation Tool. You can self-host n8n, easily extend it, and even you can use it. n8n is an extendable workflow automation tool that enables you to connect anything to everything via its open, fair-code model. Berlin, Germany n8n. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic, and apps.

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate n8n with Databricks Lakehouse in minutes

Try for free now

Prerequisites

  1. A n8n account to transfer your customer data automatically from.
  2. A Databricks Lakehouse 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 n8n and Databricks Lakehouse, for seamless data migration.

When using Airbyte to move data from n8n to Databricks Lakehouse, it extracts data from n8n using the source connector, converts it into a format Databricks Lakehouse can ingest using the provided schema, and then loads it into Databricks Lakehouse via the destination connector. This allows businesses to leverage their n8n data for advanced analytics and insights within Databricks Lakehouse, simplifying the ETL process and saving significant time and resources.

Step 1: Set up n8n as a source connector

1. Open the N8n workflow editor and create a new workflow.
2. Drag and drop the "HTTP Request" node onto the workflow canvas.
3. Double-click the "HTTP Request" node to open its settings.
4. In the "URL" field, enter the endpoint URL for your Airbyte source connector. This can be found in the Airbyte documentation for your specific connector.
5. In the "Headers" section, add the following key-value pairs:  - "Content-Type": "application/json"  - "Authorization": "Bearer {{YOUR_AIRBYTE_API_KEY}}"  Replace "{{YOUR_AIRBYTE_API_KEY}}" with your actual Airbyte API key.
6. In the "Query Parameters" section, add any necessary query parameters for your specific connector. Again, refer to the Airbyte documentation for your connector for more information.
7. Click "Save" to save the settings for the "HTTP Request" node.
8. Connect the "HTTP Request" node to the next node in your workflow.
9. Continue building your workflow as desired, using the data returned by the Airbyte source connector in subsequent nodes.

Step 2: Set up Databricks Lakehouse as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Databricks Lakehouse" connector and click on it.
4. You will be prompted to enter your Databricks Lakehouse credentials, including your account name, personal access token, and workspace ID.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your Databricks Lakehouse destination connector settings.
7. You can now use the Databricks Lakehouse connector to transfer data from your source connectors to your Databricks Lakehouse destination.
8. To set up a data transfer, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector credentials and configure your data transfer settings.
10. Once you have configured your source connector, select the Databricks Lakehouse connector as your destination and follow the prompts to configure your data transfer settings.
11. Click on the "Run" button to initiate the data transfer.

Step 3: Set up a connection to sync your n8n data to Databricks Lakehouse

Once you've successfully connected n8n as a data source and Databricks Lakehouse 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 n8n from the dropdown list of your configured sources.
  3. Select your destination: Choose Databricks Lakehouse 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 n8n objects you want to import data from towards Databricks Lakehouse. 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 n8n to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your n8n data.

Use Cases to transfer your n8n data to Databricks Lakehouse

Integrating data from n8n to Databricks Lakehouse provides several benefits. Here are a few use cases:

  1. Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your n8n data, extracting insights that wouldn't be possible within n8n alone.
  2. Data Consolidation: If you're using multiple other sources along with n8n, syncing to Databricks Lakehouse 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: n8n has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing n8n data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding n8n data.
  6. Data Science and Machine Learning: By having n8n data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While n8n provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a n8n table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a n8n account as an Airbyte data source connector.
  2. Configure Databricks Lakehouse as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from n8n to Databricks Lakehouse 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!

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

n8n
Databricks Lakehouse

Related Syncs with n8n

Tags

Analytical Platforms

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

n8n
Databricks Lakehouse

Related Syncs with n8n

N8n to AWS Datalake
N8n to BigQuery
N8n to Databricks Lakehouse
N8n to Firebolt
N8n to Redshift
N8n to S3
N8n to S3 Glue
N8n to Snowflake Data Cloud
N8n to Teradata

Tags

Analytical Platforms

Ready to get started?

Try Airbyte Cloud freeTalk to our team

Frequently Asked Questions

What data can you extract from n8n?

N8n's API provides access to a wide range of data types, including:  

1. Workflow data: This includes information about the workflows created in n8n, such as their names, descriptions, and trigger events.  
2. Node data: This includes data related to the individual nodes used in workflows, such as their names, types, and configurations.  
3. Execution data: This includes information about the execution of workflows, such as the start and end times, the status of each node, and any errors encountered.  
4. Credentials data: This includes data related to the credentials used to authenticate with external services, such as API keys and access tokens.  
5. Workflow run data: This includes data related to the runs of individual workflows, such as the input and output data, the status of each node, and any errors encountered.  
6. Node run data: This includes data related to the runs of individual nodes within workflows, such as the input and output data, the status of the node, and any errors encountered.  

Overall, n8n's API provides access to a comprehensive set of data types that can be used to monitor and manage workflows, troubleshoot issues, and optimize performance.

What data can you transfer to Databricks Lakehouse?

You can transfer a wide variety of data to Databricks Lakehouse. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from n8n to Databricks Lakehouse?

The most prominent ETL tools to transfer data from n8n to Databricks Lakehouse include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from n8n and various sources (APIs, databases, and more), transforming it efficiently, and loading it into Databricks Lakehouse and other databases, data warehouses and data lakes, enhancing data management capabilities.

What should you do next?

Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:

flag icon
Easily address your data movement needs with Airbyte Cloud
Take the first step towards extensible data movement infrastructure that will give a ton of time back to your data team. 
Get started with Airbyte for free
high five icon
Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
stars sparkling
Improve your data infrastructure knowledge
Subscribe to our monthly newsletter and get the community’s new enlightening content along with Airbyte’s progress in their mission to solve data integration once and for all.
Subscribe to newsletter

Connectors Used

n8n
Databricks Lakehouse

Related Syncs with n8n

N8n to AWS Datalake
N8n to BigQuery
N8n to Databricks Lakehouse
N8n to Firebolt
N8n to Redshift
N8n to S3
N8n to S3 Glue
N8n to Snowflake Data Cloud
N8n to Teradata

Tags

Analytical Platforms

Connectors Used

n8n
Databricks Lakehouse

Related Syncs with n8n

N8n to AWS Datalake
N8n to BigQuery
N8n to Databricks Lakehouse
N8n to Firebolt
N8n to Redshift
N8n to S3
N8n to S3 Glue
N8n to Snowflake Data Cloud
N8n to Teradata

Tags

Analytical Platforms