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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.
AppMetrica is a mobile attribution and analytics platform developed by Yandex. It is free, real-time and has no data limits restriction. AppMetrica offers accurate install attribution along with powerful and flexible analytics and crash-reporting features. We help our customers to increase the effectiveness of their marketing activities and knowthe audience better with AppMetrica insightful reports.
1. User behavior data: Yandex Appmetrica's API allows you to extract data on user behavior, such as the number of sessions, session duration, and the number of screens viewed per session.
2. User acquisition data: You can extract data on how users are acquiring your app, including the number of installs, the source of the install (e.g., organic search, paid advertising), and the cost per install.
3. User retention data: The API allows you to extract data on user retention, such as the number of users who return to your app after their first session, and the number of users who continue to use your app over time.
4. In-app purchase data: You can extract data on in-app purchases, including the number of purchases, the revenue generated from purchases, and the average purchase value.
5. Custom event data: Yandex Appmetrica's API allows you to track custom events within your app, such as button clicks or form submissions, and extract data on how often these events occur.
6. Device data: You can extract data on the devices your app is being used on, including the device type, operating system, and screen resolution.
7. Location data: The API allows you to extract data on the location of your app users, including their country, city, and language preferences.
8. Crash data: You can extract data on app crashes, including the number of crashes, the type of crash, and the device and operating system the crash occurred on.
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.
AppMetrica is a mobile attribution and analytics platform developed by Yandex. It is free, real-time and has no data limits restriction. AppMetrica offers accurate install attribution along with powerful and flexible analytics and crash-reporting features. We help our customers to increase the effectiveness of their marketing activities and knowthe audience better with AppMetrica insightful reports.
1. User behavior data: Yandex Appmetrica's API allows you to extract data on user behavior, such as the number of sessions, session duration, and the number of screens viewed per session.
2. User acquisition data: You can extract data on how users are acquiring your app, including the number of installs, the source of the install (e.g., organic search, paid advertising), and the cost per install.
3. User retention data: The API allows you to extract data on user retention, such as the number of users who return to your app after their first session, and the number of users who continue to use your app over time.
4. In-app purchase data: You can extract data on in-app purchases, including the number of purchases, the revenue generated from purchases, and the average purchase value.
5. Custom event data: Yandex Appmetrica's API allows you to track custom events within your app, such as button clicks or form submissions, and extract data on how often these events occur.
6. Device data: You can extract data on the devices your app is being used on, including the device type, operating system, and screen resolution.
7. Location data: The API allows you to extract data on the location of your app users, including their country, city, and language preferences.
8. Crash data: You can extract data on app crashes, including the number of crashes, the type of crash, and the device and operating system the crash occurred on.
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.
AppMetrica is a mobile attribution and analytics platform developed by Yandex. It is free, real-time and has no data limits restriction. AppMetrica offers accurate install attribution along with powerful and flexible analytics and crash-reporting features. We help our customers to increase the effectiveness of their marketing activities and knowthe audience better with AppMetrica insightful reports.
1. User behavior data: Yandex Appmetrica's API allows you to extract data on user behavior, such as the number of sessions, session duration, and the number of screens viewed per session.
2. User acquisition data: You can extract data on how users are acquiring your app, including the number of installs, the source of the install (e.g., organic search, paid advertising), and the cost per install.
3. User retention data: The API allows you to extract data on user retention, such as the number of users who return to your app after their first session, and the number of users who continue to use your app over time.
4. In-app purchase data: You can extract data on in-app purchases, including the number of purchases, the revenue generated from purchases, and the average purchase value.
5. Custom event data: Yandex Appmetrica's API allows you to track custom events within your app, such as button clicks or form submissions, and extract data on how often these events occur.
6. Device data: You can extract data on the devices your app is being used on, including the device type, operating system, and screen resolution.
7. Location data: The API allows you to extract data on the location of your app users, including their country, city, and language preferences.
8. Crash data: You can extract data on app crashes, including the number of crashes, the type of crash, and the device and operating system the crash occurred on.
1. Open the Yandex Appmetrica website and log in to your account.
2. Navigate to the "API Access" section in the left-hand menu.
3. Click on the "Create new token" button to generate a new API token.
4. Enter a name for the token and select the permissions you want to grant to Airbyte.
5. Click on the "Create" button to generate the token.
6. Copy the generated token to your clipboard.
7. Open the Airbyte website and navigate to the "Sources" page.
8. Click on the "Add Source" button and select "Yandex Appmetrica" from the list of available connectors.
9. Enter a name for the source and paste the API token you copied earlier into the "API Token" field.
10. Enter the ID of the Appmetrica application you want to connect to in the "Application ID" field.
11. Click on the "Test" button to verify the connection.
12. If the connection is successful, click on the "Create" button to save the source.
13. You can now use the Yandex Appmetrica source connector to extract data from your Appmetrica application and load it into your data warehouse or other destination.
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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