How to load data from Commercetools to AWS Datalake

Learn how to use Airbyte to synchronize your Commercetools data into AWS Datalake within minutes.

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Set up a Commercetools connector in Airbyte

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

Set up AWS Datalake for your extracted Commercetools data

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

Configure the Commercetools to AWS Datalake 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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How to Sync Commercetools to AWS Datalake Manually

  1. Log in to the AWS Management Console.
  2. Navigate to the S3 service and create a new bucket where you will store your data lake files.
  3. Configure the bucket settings according to your requirements (e.g., versioning, access permissions).
  4. Note down the bucket name and region for later use.
  1. Go to the IAM service in the AWS Management Console.
  2. Create a new IAM role that will be assumed by the AWS service that will interact with S3.
  3. Attach policies that grant necessary permissions to read from and write to the S3 bucket you created.
  1. Navigate to the AWS Lambda service.
  2. Create a new Lambda function with a runtime compatible with your preferred programming language (e.g., Python, Node.js).
  3. Assign the previously created IAM role to this Lambda function.
  4. Write the code for the Lambda function to interact with the commercetools API and fetch the data you want to move. You will need to handle API authentication, pagination, and error checking.
  5. Add code to format the fetched data as needed and upload it to the S3 bucket using AWS SDKs (e.g., boto3 for Python, AWS SDK for JavaScript).
  6. Configure the Lambda function’s trigger. You can schedule it to run at regular intervals using Amazon CloudWatch Events or invoke it manually.
  1. Register as a developer on the commercetools platform and obtain your project credentials (Client ID, Client Secret, Project Key, and Scopes).
  2. Use these credentials to authenticate API requests.
  3. Make API calls to commercetools to retrieve the data you need. Handle pagination if the data size is larger than what can be retrieved in a single API call.
  4. Process the data as required (e.g., convert JSON to CSV, if needed).
  1. Within the Lambda function, use the AWS SDK to create a connection to the S3 bucket.
  2. Convert your data into the desired file format (if not already in that format).
  3. Upload the data to the S3 bucket using the AWS SDK’s S3 client. Make sure to handle any potential errors during the upload process.
  4. Log the success or failure of the data upload for monitoring purposes.
  1. Test the Lambda function manually by invoking it from the AWS Console or using the AWS CLI.
  2. Verify that the data is being fetched correctly from commercetools and uploaded to the S3 bucket.
  3. Check the logs for any errors or issues that need to be addressed.
  1. Set up CloudWatch alarms to monitor the Lambda function’s execution and to alert you in case of failures.
  2. Regularly check the logs for any errors or unexpected behavior.
  3. Update the Lambda function code and IAM policies as needed to accommodate any changes in the commercetools API or your AWS infrastructure.

Additional Considerations

  • Ensure that your Lambda function has error handling and retry logic in place to handle any transient issues with the API or the network.
  • Consider the security of your data in transit and at rest. You may want to encrypt the data before uploading it to S3 and ensure that the bucket is secured.
  • Monitor the costs associated with AWS services used in this process and optimize as necessary.
  • Keep your commercetools and AWS credentials secure and rotate them periodically.
  • If your data set is large, consider using AWS Glue or a similar service to orchestrate the data movement and transformation tasks.

How to Sync Commercetools to AWS Datalake Manually - Method 2:

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.

Commercetools is a cloud-based headless commerce platform that provides APIs to power e-commerce sales and similar functions for large businesses. Both the company and platform are called Commercetools. The company is headquartered in Munich, Germany with additional offices in Berlin, Germany; Jena, Germany; Amsterdam, Netherlands; London, England and etc. Through its investor REWE Group, it is associated with the omnichannel order fulfillment software solutions providers fulfillmenttools and the payment transactions provider paymenttools. Its clients include Audi, Bang & Olufsen, Carhartt and Nuts.com.

Commercetools's API provides access to a wide range of data related to e-commerce and retail operations. The following are the categories of data that can be accessed through Commercetools's API:  

1. Product data: This includes information about products such as name, description, price, availability, and images.  
2. Customer data: This includes information about customers such as name, email address, shipping address, and order history.  
3. Order data: This includes information about orders such as order number, customer information, product information, and shipping details.  
4. Inventory data: This includes information about inventory levels, stock availability, and stock locations.  
5. Payment data: This includes information about payment methods, payment status, and transaction details.  
6. Shipping data: This includes information about shipping methods, shipping rates, and delivery status.  
7. Tax data: This includes information about tax rates, tax rules, and tax exemptions.  
8. Analytics data: This includes information about website traffic, customer behavior, and sales performance.  

Overall, Commercetools's API provides access to a comprehensive set of data that can help businesses optimize their e-commerce and retail operations.

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 Commercetools to AWS Datalake 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 Commercetools to AWS Datalake 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.

What should you do next?

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

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Connectors Used

Commercetools
AWS Datalake

Related Syncs with Commercetools

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

Tags

Amazon Web Services
Back to all tutorials
Warehouses and Lakes
Finance & Ops Analytics

How to load data from Commercetools to AWS Datalake

Learn how to use Airbyte to synchronize your Commercetools data into AWS Datalake within minutes.

TL;DR
What is Commercetools
What is AWS Datalake
Prerequisites
Step 1: Setup Commercetools
Step 2: Setup AWS Datalake
Step 3: Setup a connectionUse CasesWrapping Up
Example H2
Example H3

Sync data between Commercetools and AWS Datalake

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 Commercetools as a source connector (using Auth, or usually an API key)
  2. set up AWS Datalake 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 Commercetools

Commercetools is a cloud-based headless commerce platform that provides APIs to power e-commerce sales and similar functions for large businesses. Both the company and platform are called Commercetools. The company is headquartered in Munich, Germany with additional offices in Berlin, Germany; Jena, Germany; Amsterdam, Netherlands; London, England and etc. Through its investor REWE Group, it is associated with the omnichannel order fulfillment software solutions providers fulfillmenttools and the payment transactions provider paymenttools. Its clients include Audi, Bang & Olufsen, Carhartt and Nuts.com.

What is AWS Datalake

An AWS Data Lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. It is designed to handle massive amounts of data from various sources, such as databases, applications, IoT devices, and more. With AWS Data Lake, you can easily ingest, store, catalog, process, and analyze data using a wide range of AWS services like Amazon S3, Amazon Athena, AWS Glue, and Amazon EMR. This allows you to build data lakes for machine learning, big data analytics, and data warehousing workloads. AWS Data Lake provides a secure, scalable, and cost-effective solution for managing your organization's data.

Integrate Commercetools with AWS Datalake in minutes

Try for free now

Prerequisites

  1. A Commercetools account to transfer your customer data automatically from.
  2. A AWS Datalake 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 Commercetools and AWS Datalake, for seamless data migration.

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

Step 1: Set up Commercetools as a source connector

1. First, you need to obtain your Commercetools credentials, which include the client ID, client secret, project key, and API URL. You can find these credentials in your Commercetools account under the "API Clients" section.  
2. Once you have your Commercetools credentials, go to the Airbyte dashboard and click on "Sources" on the left-hand side menu.  
3. Click on the "Commercetools" source connector and then click on "Create new connection."  
4. In the "Connection Configuration" page, enter your Commercetools credentials in the appropriate fields. Make sure to enter the correct API URL for your Commercetools account.  
5. Click on "Test Connection" to ensure that Airbyte can connect to your Commercetools account.  
6. If the connection is successful, click on "Save & Continue."  
7. In the "Sync Configuration" page, you can configure how often you want Airbyte to sync data from your Commercetools account. You can also choose which data you want to sync.  
8. Once you have configured the sync settings, click on "Save & Continue."  
9. Finally, click on "Create Connection" to create the Commercetools source connector on Airbyte.  
10. You can now use the Commercetools source connector to extract data from your Commercetools account and load it into your destination data warehouse or data lake.

Step 2: Set up AWS Datalake as a destination connector

1. Log in to your AWS account and navigate to the AWS Management Console.
2. Click on the S3 service and create a new bucket where you will store your data.
3. Create an IAM user with the necessary permissions to access the S3 bucket. Make sure to save the access key and secret key.
4. Open Airbyte and navigate to the Destinations tab.
5. Select the AWS Datalake destination connector and click on "Create new connection".
6. Enter a name for your connection and paste the access key and secret key you saved earlier.
7. Enter the name of the S3 bucket you created in step 2 and select the region where it is located.
8. Choose the format in which you want your data to be stored in the S3 bucket (e.g. CSV, JSON, Parquet).
9. Configure any additional settings, such as compression or encryption, if necessary.
10. Test the connection to make sure it is working properly.
11. Save the connection and start syncing your data to the AWS Datalake.

Step 3: Set up a connection to sync your Commercetools data to AWS Datalake

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

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

Use Cases to transfer your Commercetools data to AWS Datalake

Integrating data from Commercetools to AWS Datalake provides several benefits. Here are a few use cases:

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

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Commercetools account as an Airbyte data source connector.
  2. Configure AWS Datalake as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Commercetools to AWS Datalake 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:

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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
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Talk to a data infrastructure expert
Get a free consultation with an Airbyte expert to significantly improve your data movement infrastructure. 
Talk to sales
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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

Commercetools
AWS Datalake

Related Syncs with Commercetools

Tags

Amazon Web Services

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

Commercetools
AWS Datalake

Related Syncs with Commercetools

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

Tags

Amazon Web Services

Ready to get started?

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Frequently Asked Questions

What data can you extract from Commercetools?

Commercetools's API provides access to a wide range of data related to e-commerce and retail operations. The following are the categories of data that can be accessed through Commercetools's API:  

1. Product data: This includes information about products such as name, description, price, availability, and images.  
2. Customer data: This includes information about customers such as name, email address, shipping address, and order history.  
3. Order data: This includes information about orders such as order number, customer information, product information, and shipping details.  
4. Inventory data: This includes information about inventory levels, stock availability, and stock locations.  
5. Payment data: This includes information about payment methods, payment status, and transaction details.  
6. Shipping data: This includes information about shipping methods, shipping rates, and delivery status.  
7. Tax data: This includes information about tax rates, tax rules, and tax exemptions.  
8. Analytics data: This includes information about website traffic, customer behavior, and sales performance.  

Overall, Commercetools's API provides access to a comprehensive set of data that can help businesses optimize their e-commerce and retail operations.

What data can you transfer to AWS Datalake?

You can transfer a wide variety of data to AWS Datalake. 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 Commercetools to AWS Datalake?

The most prominent ETL tools to transfer data from Commercetools to AWS Datalake include:

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

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