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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: Branch's API allows you to extract user data such as user ID, name, email address, and other relevant information.
2. App data: You can extract data related to your app, such as app ID, app name, and app version.
3. Event data: Branch's API allows you to extract data related to user events, such as app installs, app opens, and other custom events.
4. Attribution data: You can extract data related to user attribution, such as the source of the user's install or the campaign that led to the user's conversion.
5. Link data: Branch's API allows you to extract data related to links, such as link clicks, link conversions, and link metadata.
6. Deep linking data: You can extract data related to deep linking, such as the deep link URL, the app that the user was deep linked into, and other relevant information.
7. Referral data: Branch's API allows you to extract data related to referrals, such as the number of referrals, the users who referred others, and other relevant information.
8. Conversion data: You can extract data related to user conversions, such as the number of conversions, the conversion rate, and other relevant information.
9. Revenue data: Branch's API allows you to extract data related to revenue, such as the total revenue generated by your app, the revenue generated by each user, and other relevant information.
10. Custom data: You can extract custom data that you have added to your app, such as user preferences, user behavior, and other relevant information.
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: Branch's API allows you to extract user data such as user ID, name, email address, and other relevant information.
2. App data: You can extract data related to your app, such as app ID, app name, and app version.
3. Event data: Branch's API allows you to extract data related to user events, such as app installs, app opens, and other custom events.
4. Attribution data: You can extract data related to user attribution, such as the source of the user's install or the campaign that led to the user's conversion.
5. Link data: Branch's API allows you to extract data related to links, such as link clicks, link conversions, and link metadata.
6. Deep linking data: You can extract data related to deep linking, such as the deep link URL, the app that the user was deep linked into, and other relevant information.
7. Referral data: Branch's API allows you to extract data related to referrals, such as the number of referrals, the users who referred others, and other relevant information.
8. Conversion data: You can extract data related to user conversions, such as the number of conversions, the conversion rate, and other relevant information.
9. Revenue data: Branch's API allows you to extract data related to revenue, such as the total revenue generated by your app, the revenue generated by each user, and other relevant information.
10. Custom data: You can extract custom data that you have added to your app, such as user preferences, user behavior, and other relevant information.
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: Branch's API allows you to extract user data such as user ID, name, email address, and other relevant information.
2. App data: You can extract data related to your app, such as app ID, app name, and app version.
3. Event data: Branch's API allows you to extract data related to user events, such as app installs, app opens, and other custom events.
4. Attribution data: You can extract data related to user attribution, such as the source of the user's install or the campaign that led to the user's conversion.
5. Link data: Branch's API allows you to extract data related to links, such as link clicks, link conversions, and link metadata.
6. Deep linking data: You can extract data related to deep linking, such as the deep link URL, the app that the user was deep linked into, and other relevant information.
7. Referral data: Branch's API allows you to extract data related to referrals, such as the number of referrals, the users who referred others, and other relevant information.
8. Conversion data: You can extract data related to user conversions, such as the number of conversions, the conversion rate, and other relevant information.
9. Revenue data: Branch's API allows you to extract data related to revenue, such as the total revenue generated by your app, the revenue generated by each user, and other relevant information.
10. Custom data: You can extract custom data that you have added to your app, such as user preferences, user behavior, and other relevant information.
1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Connect" button next to the Branch source connector.
3. In the "New Branch Source" window that appears, enter a name for your source and click "Next".
4. Enter your Branch API key and secret in the appropriate fields. You can find these credentials in your Branch account under "API Keys" in the dashboard.
5. Click "Test" to ensure that the credentials are valid and that Airbyte can connect to your Branch account.
6. Once the test is successful, click "Save" to add the Branch source connector to your Airbyte workspace.
7. You can now configure the source connector by selecting the tables and columns you want to replicate from your Branch account.
8. Click "Create Connection" to start the replication process and begin syncing your Branch data with your destination data warehouse or storage solution.
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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