Google Drive is a cloud storage service that allows users to store, sync, and share files online. It offers collaborative tools and integrates with Google Workspace, enhancing productivity.
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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
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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
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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. File metadata: The API allows you to extract information about files stored in Google Drive, such as the file name, size, creation date, and modification date.
2. File content: You can extract the content of files stored in Google Drive, such as text, images, and videos.
3. File sharing information: The API allows you to extract information about who has access to a file, including their email addresses and permission levels.
4. User information: You can extract information about the users who have access to a file, such as their email addresses and profile pictures.
5. Folder structure: The API allows you to extract information about the folder structure of a user's Google Drive, including the names and IDs of folders.
6. Revision history: You can extract information about the revision history of a file, including the date and time of each revision and the user who made the revision.
7. Comments: The API allows you to extract information about comments made on a file, including the text of the comment, the user who made the comment, and the date and time of the comment.
8. Activity: You can extract information about the activity on a file, including when it was last viewed, edited, or shared.
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. File metadata: The API allows you to extract information about files stored in Google Drive, such as the file name, size, creation date, and modification date.
2. File content: You can extract the content of files stored in Google Drive, such as text, images, and videos.
3. File sharing information: The API allows you to extract information about who has access to a file, including their email addresses and permission levels.
4. User information: You can extract information about the users who have access to a file, such as their email addresses and profile pictures.
5. Folder structure: The API allows you to extract information about the folder structure of a user's Google Drive, including the names and IDs of folders.
6. Revision history: You can extract information about the revision history of a file, including the date and time of each revision and the user who made the revision.
7. Comments: The API allows you to extract information about comments made on a file, including the text of the comment, the user who made the comment, and the date and time of the comment.
8. Activity: You can extract information about the activity on a file, including when it was last viewed, edited, or shared.
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. File metadata: The API allows you to extract information about files stored in Google Drive, such as the file name, size, creation date, and modification date.
2. File content: You can extract the content of files stored in Google Drive, such as text, images, and videos.
3. File sharing information: The API allows you to extract information about who has access to a file, including their email addresses and permission levels.
4. User information: You can extract information about the users who have access to a file, such as their email addresses and profile pictures.
5. Folder structure: The API allows you to extract information about the folder structure of a user's Google Drive, including the names and IDs of folders.
6. Revision history: You can extract information about the revision history of a file, including the date and time of each revision and the user who made the revision.
7. Comments: The API allows you to extract information about comments made on a file, including the text of the comment, the user who made the comment, and the date and time of the comment.
8. Activity: You can extract information about the activity on a file, including when it was last viewed, edited, or shared.
1. Go to the Airbyte dashboard and click on "Sources" on the left-hand side of the screen.
2. Click on the "Create New Source" button and select "Google Drive" from the list of available connectors.
3. Enter a name for your Google Drive source and click on "Next".
4. You will be prompted to enter your Google Drive credentials. Click on "Add New Account" and enter your Google email address and password.
5. Once you have entered your credentials, click on "Authorize" to allow Airbyte to access your Google Drive account.
6. Select the folders or files you want to sync with Airbyte by clicking on the checkboxes next to them.
7. Click on "Test" to ensure that your Google Drive source is working properly.
8. If the test is successful, click on "Create Source" to save your Google Drive source in Airbyte.
9. You can now use your Google Drive source to create data integrations and sync your data with other destinations.
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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