Top companies trust Airbyte to centralize their Data
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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.
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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.
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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.
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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
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Cover your custom needs with our extensibility
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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
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Reliability at every level
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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
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Cover your custom needs with our extensibility
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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
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Reliability at every level
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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
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Cover your custom needs with our extensibility
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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
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Reliability at every level
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Move large volumes, fast.
Change Data Capture.
Security from source to destination.
We support the CDC methods your company needs
Log-based CDC
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Timestamp-based CDC
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Airbyte Open Source
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Airbyte Cloud
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Airbyte Enterprise
Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
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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.
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White-glove enterprise-level support
Including for your Airbyte Open Source instance with our premium support.
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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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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.
1. Social media metrics: Falcon.io's API allows you to extract data on various social media metrics such as likes, comments, shares, and followers across different social media platforms.
2. Engagement rates: You can also extract data on engagement rates, which is the percentage of people who interact with your social media content.
3. Sentiment analysis: Falcon.io's API provides sentiment analysis data, which helps you understand the overall sentiment of your brand or product on social media.
4. Audience demographics: You can extract data on the demographics of your social media audience, including age, gender, location, and interests.
5. Influencer data: Falcon.io's API allows you to extract data on influencers who are engaging with your brand or product on social media.
6. Content performance: You can extract data on the performance of your social media content, including reach, impressions, and engagement.
7. Competitor analysis: Falcon.io's API provides data on your competitors' social media performance, including their engagement rates, audience demographics, and content performance.
8. Campaign performance: You can extract data on the performance of your social media campaigns, including the number of clicks, conversions, and ROI.
9. Customer service metrics: Falcon.io's API allows you to extract data on your customer service metrics, including response time, resolution rate, and customer satisfaction.
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. Social media metrics: Falcon.io's API allows you to extract data on various social media metrics such as likes, comments, shares, and followers across different social media platforms.
2. Engagement rates: You can also extract data on engagement rates, which is the percentage of people who interact with your social media content.
3. Sentiment analysis: Falcon.io's API provides sentiment analysis data, which helps you understand the overall sentiment of your brand or product on social media.
4. Audience demographics: You can extract data on the demographics of your social media audience, including age, gender, location, and interests.
5. Influencer data: Falcon.io's API allows you to extract data on influencers who are engaging with your brand or product on social media.
6. Content performance: You can extract data on the performance of your social media content, including reach, impressions, and engagement.
7. Competitor analysis: Falcon.io's API provides data on your competitors' social media performance, including their engagement rates, audience demographics, and content performance.
8. Campaign performance: You can extract data on the performance of your social media campaigns, including the number of clicks, conversions, and ROI.
9. Customer service metrics: Falcon.io's API allows you to extract data on your customer service metrics, including response time, resolution rate, and customer satisfaction.
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. Social media metrics: Falcon.io's API allows you to extract data on various social media metrics such as likes, comments, shares, and followers across different social media platforms.
2. Engagement rates: You can also extract data on engagement rates, which is the percentage of people who interact with your social media content.
3. Sentiment analysis: Falcon.io's API provides sentiment analysis data, which helps you understand the overall sentiment of your brand or product on social media.
4. Audience demographics: You can extract data on the demographics of your social media audience, including age, gender, location, and interests.
5. Influencer data: Falcon.io's API allows you to extract data on influencers who are engaging with your brand or product on social media.
6. Content performance: You can extract data on the performance of your social media content, including reach, impressions, and engagement.
7. Competitor analysis: Falcon.io's API provides data on your competitors' social media performance, including their engagement rates, audience demographics, and content performance.
8. Campaign performance: You can extract data on the performance of your social media campaigns, including the number of clicks, conversions, and ROI.
9. Customer service metrics: Falcon.io's API allows you to extract data on your customer service metrics, including response time, resolution rate, and customer satisfaction.
1. First, navigate to the Falcon.io source connector page on Airbyte.com.
2. Click on the "Create New Connection" button.
3. In the "Configuration" tab, enter a name for your connection.
4. In the "Source" section, select "Falcon.io" from the dropdown menu.
5. In the "Authentication" section, enter your Falcon.io API credentials, including your API key and secret.
6. In the "Advanced" section, you can configure additional settings such as the number of threads to use for syncing data.
7. Click on the "Test" button to ensure that your credentials are correct and that the connection is working properly.
8. If the test is successful, click on the "Save & Continue" button to proceed to the next step.
9. In the "Schema" tab, you can select which tables you want to sync data from.
10. Once you have selected the tables you want to sync, click on the "Save & Continue" button to proceed to the final step.
11. In the "Sync" tab, you can configure the frequency and scheduling of your data syncs.
12. Once you have configured your sync settings, click on the "Save & Run" button to start syncing data from Falcon.io to your 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.