Top companies trust Airbyte to centralize their Data
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 300+ 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 connector builder.
Configure the connection in Airbyte
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
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.
Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.
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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.
Facebook Pages permits businesses to promote their brand, grow their audience and start conversations with customers and people interested in learning more. A Facebook Page is where customers go to discover and engage with your business. Setting up a Page is simple and free, and it looks great on both desktop. A Facebook page is a public profile specifically created for businesses, brands, celebrities, causes, and other organizations. It provides a way for businesses and other organizations to interact with rather than just advertise to potential.
The Facebook Pages API provides access to a wide range of data related to Facebook Pages. The following are the categories of data that can be accessed through the API:
1. Page Information: This includes basic information about the page such as name, category, description, and contact information.
2. Posts: This includes all the posts made by the page, including status updates, photos, videos, and links.
3. Comments: This includes all the comments made on the page's posts.
4. Reactions: This includes the number of likes, loves, wows, hahas, sads, and angries on the page's posts.
5. Insights: This includes data related to the page's performance, such as reach, engagement, and follower demographics.
6. Messages: This includes all the messages sent to the page by users.
7. Reviews: This includes all the reviews left by users on the page.
8. Events: This includes all the events created by the page.
9. Videos: This includes all the videos uploaded by the page.
10. Photos: This includes all the photos uploaded by the page.
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.
Facebook Pages permits businesses to promote their brand, grow their audience and start conversations with customers and people interested in learning more. A Facebook Page is where customers go to discover and engage with your business. Setting up a Page is simple and free, and it looks great on both desktop. A Facebook page is a public profile specifically created for businesses, brands, celebrities, causes, and other organizations. It provides a way for businesses and other organizations to interact with rather than just advertise to potential.
The Facebook Pages API provides access to a wide range of data related to Facebook Pages. The following are the categories of data that can be accessed through the API:
1. Page Information: This includes basic information about the page such as name, category, description, and contact information.
2. Posts: This includes all the posts made by the page, including status updates, photos, videos, and links.
3. Comments: This includes all the comments made on the page's posts.
4. Reactions: This includes the number of likes, loves, wows, hahas, sads, and angries on the page's posts.
5. Insights: This includes data related to the page's performance, such as reach, engagement, and follower demographics.
6. Messages: This includes all the messages sent to the page by users.
7. Reviews: This includes all the reviews left by users on the page.
8. Events: This includes all the events created by the page.
9. Videos: This includes all the videos uploaded by the page.
10. Photos: This includes all the photos uploaded by the page.
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.
Facebook Pages permits businesses to promote their brand, grow their audience and start conversations with customers and people interested in learning more. A Facebook Page is where customers go to discover and engage with your business. Setting up a Page is simple and free, and it looks great on both desktop. A Facebook page is a public profile specifically created for businesses, brands, celebrities, causes, and other organizations. It provides a way for businesses and other organizations to interact with rather than just advertise to potential.
The Facebook Pages API provides access to a wide range of data related to Facebook Pages. The following are the categories of data that can be accessed through the API:
1. Page Information: This includes basic information about the page such as name, category, description, and contact information.
2. Posts: This includes all the posts made by the page, including status updates, photos, videos, and links.
3. Comments: This includes all the comments made on the page's posts.
4. Reactions: This includes the number of likes, loves, wows, hahas, sads, and angries on the page's posts.
5. Insights: This includes data related to the page's performance, such as reach, engagement, and follower demographics.
6. Messages: This includes all the messages sent to the page by users.
7. Reviews: This includes all the reviews left by users on the page.
8. Events: This includes all the events created by the page.
9. Videos: This includes all the videos uploaded by the page.
10. Photos: This includes all the photos uploaded by the page.
1. Go to the Facebook Developers website and create a new app.
2. Once you have created the app, go to the app dashboard and select "Add Product" on the left-hand side.
3. Select "Facebook Login" and then "Set Up".
4. Choose "Web" as the platform and enter the URL of your Airbyte instance as the "Site URL".
5. Save the changes and go to the "Settings" tab on the left-hand side.
6. Under "Basic", copy the "App ID" and "App Secret" values.
7. Go to your Airbyte instance and select "Sources" from the left-hand side menu.
8. Click "New Source" and select "Facebook Pages" from the list.
9. Enter the "App ID" and "App Secret" values in the appropriate fields.
10. Click "Test Connection" to ensure that the credentials are correct.
11. Once the connection is successful, select the Facebook Pages that you want to sync data from.
12. Choose the frequency of data sync and any other relevant settings.
13. Save the source and start syncing data from your Facebook Pages.
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.
