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.
Ready to get started?
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.
Unleash is a global innovation lab that brings together entrepreneurs, investors, and corporations to collaborate on solutions to some of the world's most pressing challenges. The program focuses on themes such as sustainable energy, food security, and healthcare, and provides participants with access to mentorship, funding, and resources to develop their ideas into viable businesses. Unleash also emphasizes diversity and inclusion, with a goal of bringing together individuals from diverse backgrounds and perspectives to drive innovation and create positive social impact. The program culminates in a week-long innovation lab where participants pitch their ideas and collaborate on solutions to global challenges.
Unleash's API provides access to various types of data related to feature flags and experimentation. The following are the categories of data that can be accessed through the API:
1. Feature flags: The API provides access to all the feature flags created in the Unleash dashboard, including their names, descriptions, and configurations.
2. Metrics: The API provides access to various metrics related to feature flags, such as the number of times a feature flag was evaluated, the number of times it was enabled, and the percentage of users who saw the feature flag.
3. Events: The API provides access to events related to feature flags, such as when a feature flag was toggled on or off, when it was evaluated, and when it was enabled or disabled.
4. User targeting: The API provides access to user targeting information, such as the rules used to target specific users for a feature flag and the percentage of users who were targeted.
5. Experiments: The API provides access to information related to experiments, such as the name of the experiment, the variations being tested, and the metrics being tracked.
Overall, Unleash's API provides a comprehensive set of data related to feature flags and experimentation, allowing developers to gain insights into how their features are performing and make data-driven decisions.
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.
Unleash is a global innovation lab that brings together entrepreneurs, investors, and corporations to collaborate on solutions to some of the world's most pressing challenges. The program focuses on themes such as sustainable energy, food security, and healthcare, and provides participants with access to mentorship, funding, and resources to develop their ideas into viable businesses. Unleash also emphasizes diversity and inclusion, with a goal of bringing together individuals from diverse backgrounds and perspectives to drive innovation and create positive social impact. The program culminates in a week-long innovation lab where participants pitch their ideas and collaborate on solutions to global challenges.
Unleash's API provides access to various types of data related to feature flags and experimentation. The following are the categories of data that can be accessed through the API:
1. Feature flags: The API provides access to all the feature flags created in the Unleash dashboard, including their names, descriptions, and configurations.
2. Metrics: The API provides access to various metrics related to feature flags, such as the number of times a feature flag was evaluated, the number of times it was enabled, and the percentage of users who saw the feature flag.
3. Events: The API provides access to events related to feature flags, such as when a feature flag was toggled on or off, when it was evaluated, and when it was enabled or disabled.
4. User targeting: The API provides access to user targeting information, such as the rules used to target specific users for a feature flag and the percentage of users who were targeted.
5. Experiments: The API provides access to information related to experiments, such as the name of the experiment, the variations being tested, and the metrics being tracked.
Overall, Unleash's API provides a comprehensive set of data related to feature flags and experimentation, allowing developers to gain insights into how their features are performing and make data-driven decisions.
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.
Unleash is a global innovation lab that brings together entrepreneurs, investors, and corporations to collaborate on solutions to some of the world's most pressing challenges. The program focuses on themes such as sustainable energy, food security, and healthcare, and provides participants with access to mentorship, funding, and resources to develop their ideas into viable businesses. Unleash also emphasizes diversity and inclusion, with a goal of bringing together individuals from diverse backgrounds and perspectives to drive innovation and create positive social impact. The program culminates in a week-long innovation lab where participants pitch their ideas and collaborate on solutions to global challenges.
Unleash's API provides access to various types of data related to feature flags and experimentation. The following are the categories of data that can be accessed through the API:
1. Feature flags: The API provides access to all the feature flags created in the Unleash dashboard, including their names, descriptions, and configurations.
2. Metrics: The API provides access to various metrics related to feature flags, such as the number of times a feature flag was evaluated, the number of times it was enabled, and the percentage of users who saw the feature flag.
3. Events: The API provides access to events related to feature flags, such as when a feature flag was toggled on or off, when it was evaluated, and when it was enabled or disabled.
4. User targeting: The API provides access to user targeting information, such as the rules used to target specific users for a feature flag and the percentage of users who were targeted.
5. Experiments: The API provides access to information related to experiments, such as the name of the experiment, the variations being tested, and the metrics being tracked.
Overall, Unleash's API provides a comprehensive set of data related to feature flags and experimentation, allowing developers to gain insights into how their features are performing and make data-driven decisions.
1. First, navigate to the Airbyte website and create an account.
2. Once you have logged in, click on the ""Sources"" tab on the left-hand side of the screen.
3. Scroll down until you find the ""Unleash"" source connector and click on it.
4. Click on the ""Create Connection"" button to begin setting up your Unleash source connector.
5. Enter the necessary information, such as the name of your connection and your Unleash API key.
6. Choose the tables you want to sync from Unleash to Airbyte.
7. Test the connection to ensure that it is working properly.
8. Once you have successfully tested the connection, click on the ""Create Connection"" button to finalize the setup.
9. Your Unleash source connector is now connected to Airbyte and ready to start syncing data.
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.
