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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.
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.
Set up a source connector to extract data from in Airbyte
Choose from one of 400 sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code no-code connector builder.
Configure the connection in Airbyte
The Airbyte Open Data Movement Platform
The only open solution empowering data teams to meet growing business demands in the new AI era.
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Ship more quickly with the only solution that fits ALL your needs.
As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
Leverage the largest catalog of connectors
Cover your custom needs with our extensibility
Free your time from maintaining connectors, with automation
- Automated schema change handling, data normalization and more
- Automated data transformation orchestration with our dbt integration
- Automated workflow with our Airflow, Dagster and Prefect integration
Reliability at every level
Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
Timestamp-based CDC
Airbyte Open Source
Airbyte Cloud
Airbyte Enterprise
Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
Get Airbyte hosted where you need it to be
- Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.
Airbyte supports a growing list of sources, including API tools, cloud data warehouses, lakes, databases, and files, or even custom sources you can build.
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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.
1. User data: The Saasquatch API allows you to extract user data such as name, email address, and other relevant information.
2. Referral data: You can extract data related to referrals made by users, including the referral code, referral link, and the number of successful referrals.
3. Reward data: The API also provides information on rewards earned by users, including the type of reward, the amount, and the date it was earned.
4. Campaign data: You can extract data related to campaigns, including the campaign name, start and end dates, and the number of participants.
5. Analytics data: The API provides analytics data such as the number of clicks, conversions, and revenue generated by a campaign.
6. Integration data: You can extract data related to integrations with other platforms, including the type of integration, the date it was set up, and any relevant configuration details.
7. User activity data: The API allows you to extract data related to user activity, including the number of logins, referrals made, and rewards earned.
8. Program settings data: You can extract data related to program settings, including the program name, program rules, and any relevant configuration details.
9. Payment data: The API provides information on payments made to users, including the payment amount, date, and payment method.
10. User feedback data: You can extract data related to user feedback, including ratings, reviews, and comments.
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.
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.
1. User data: The Saasquatch API allows you to extract user data such as name, email address, and other relevant information.
2. Referral data: You can extract data related to referrals made by users, including the referral code, referral link, and the number of successful referrals.
3. Reward data: The API also provides information on rewards earned by users, including the type of reward, the amount, and the date it was earned.
4. Campaign data: You can extract data related to campaigns, including the campaign name, start and end dates, and the number of participants.
5. Analytics data: The API provides analytics data such as the number of clicks, conversions, and revenue generated by a campaign.
6. Integration data: You can extract data related to integrations with other platforms, including the type of integration, the date it was set up, and any relevant configuration details.
7. User activity data: The API allows you to extract data related to user activity, including the number of logins, referrals made, and rewards earned.
8. Program settings data: You can extract data related to program settings, including the program name, program rules, and any relevant configuration details.
9. Payment data: The API provides information on payments made to users, including the payment amount, date, and payment method.
10. User feedback data: You can extract data related to user feedback, including ratings, reviews, and comments.
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.
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.
1. User data: The Saasquatch API allows you to extract user data such as name, email address, and other relevant information.
2. Referral data: You can extract data related to referrals made by users, including the referral code, referral link, and the number of successful referrals.
3. Reward data: The API also provides information on rewards earned by users, including the type of reward, the amount, and the date it was earned.
4. Campaign data: You can extract data related to campaigns, including the campaign name, start and end dates, and the number of participants.
5. Analytics data: The API provides analytics data such as the number of clicks, conversions, and revenue generated by a campaign.
6. Integration data: You can extract data related to integrations with other platforms, including the type of integration, the date it was set up, and any relevant configuration details.
7. User activity data: The API allows you to extract data related to user activity, including the number of logins, referrals made, and rewards earned.
8. Program settings data: You can extract data related to program settings, including the program name, program rules, and any relevant configuration details.
9. Payment data: The API provides information on payments made to users, including the payment amount, date, and payment method.
10. User feedback data: You can extract data related to user feedback, including ratings, reviews, and comments.
1. Open the Saasquatch source connector page on Airbyte.com.
2. Click on the "Create new connection" button.
3. Enter a name for your connection and click on "Next".
4. Enter your Saasquatch API key and API secret in the respective fields.
5. Click on "Test connection" to ensure that the credentials are correct and the connection is established.
6. Once the connection is successful, click on "Next".
7. Select the tables that you want to replicate from Saasquatch to Airbyte.
8. Choose the replication frequency and the sync mode.
9. Click on "Create connection" to save the configuration.
10. Your Saasquatch source connector is now connected to Airbyte and ready to replicate data.
Note: It is important to ensure that the API key and API secret are correct and have the necessary permissions to access the required data. Also, make sure to choose the appropriate replication frequency and sync mode based on your use case.
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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