Warehouses and Lakes
Sales & Support Analytics

How to load data from Sugar CRM to AWS Datalake

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


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 Sugar CRM 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 Sugar CRM

Sugar CRM is a customer relationship management platform designed to provide businesses with the solutions needed to create, build, and maintain exceptional customer relationships. Designated a “visionary” company by leading market analysts, Sugar lays claim to a client base of more than 1.5 million customers in 120 different countries. Sugar’s goal is to empower customers with an intuitive, engaging, and immersive user experience that optimizes the social capabilities afforded by modern technology.

What is AWS Datalake


  1. A Sugar CRM 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 Sugar CRM and AWS Datalake, for seamless data migration.

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

Step 1: Set up Sugar CRM as a source connector

1. First, navigate to the "Sources" tab on the Airbyte dashboard and click "New Source".
2. Select "Sugar CRM" from the list of available sources.
3. Enter a name for the source and click "Next".
4. Enter the URL for your Sugar CRM instance, along with your username and password.
5. Click "Test Connection" to ensure that the credentials are correct and the connection is successful.
6. Once the connection is verified, select the tables you want to replicate and click "Next".
7. Choose the frequency at which you want the data to be replicated and click "Next".
8. Review the settings and click "Create Source" to complete the process.
9. You can now view and manage your Sugar CRM source connector from the "Sources" tab on the Airbyte dashboard.

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 Sugar CRM data to AWS Datalake

Once you've successfully connected Sugar CRM 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 Sugar CRM 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 Sugar CRM 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 Sugar CRM 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 Sugar CRM data.

Use Cases to transfer your Sugar CRM data to AWS Datalake

Integrating data from Sugar CRM 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 Sugar CRM data, extracting insights that wouldn't be possible within Sugar CRM alone.
  2. Data Consolidation: If you're using multiple other sources along with Sugar CRM, syncing to AWS Datalake allows you to centralize your data for a holistic view of your operations
  3. Historical Data Analysis: Sugar CRM 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 Sugar CRM 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 Sugar CRM data.
  6. Data Science and Machine Learning: By having Sugar CRM 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 Sugar CRM provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to AWS Datalake, providing more advanced business intelligence options.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Sugar CRM 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 Sugar CRM 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!

Frequently Asked Questions

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 data can you extract from Sugar CRM?

Sugar CRM's API provides access to a wide range of data related to customer relationship management. The following are the categories of data that can be accessed through Sugar CRM's API:  

1. Accounts: This includes information about the companies or organizations that are customers of the business.  
2. Contacts: This includes information about the individuals who are associated with the accounts, such as their names, contact details, and job titles.  
3. Leads: This includes information about potential customers who have shown interest in the business's products or services.  
4. Opportunities: This includes information about potential sales deals with customers, including the value of the deal, the stage of the sales process, and the probability of closing the deal.  
5. Cases: This includes information about customer support cases, such as the nature of the issue, the status of the case, and any related communications.  
6. Activities: This includes information about the interactions between the business and its customers, such as meetings, calls, and emails.  
7. Reports: This includes data related to the performance of the business, such as sales figures, customer satisfaction ratings, and marketing campaign results.  

Overall, Sugar CRM's API provides access to a comprehensive set of data that can help businesses manage their customer relationships more effectively.

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 Sugar CRM to AWS Datalake?

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

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

These tools help in extracting data from Sugar CRM 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.

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.