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.
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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.
Taking the customer relationship management (CRM) platform up a notch, Zendesk Sunshine makes it possible for businesses to connect the dots to build the full picture of their customer from data anywhere. Offering much more than the old legacy CRM platform, Zendesk Sunshine takes a new and more modern approach, native to AWS, that provides the tools needed for developers and admins to create superior customer experiences.
Zendesk Sunshine's API provides access to a wide range of data categories, including:
1. Customer data: This includes information about customers such as their name, email address, phone number, and other contact details.
2. Ticket data: This includes information about customer support tickets, such as the status of the ticket, the customer's issue, and any notes or comments added by support agents.
3. Agent data: This includes information about support agents, such as their name, email address, and performance metrics.
4. Analytics data: This includes data about customer support performance, such as response times, ticket volume, and customer satisfaction ratings.
5. Integration data: This includes data about integrations with other systems, such as CRM or marketing automation platforms.
6. Custom data: This includes any custom data fields that have been added to the Zendesk platform, such as customer preferences or product information.
Overall, Zendesk Sunshine's API provides access to a wide range of data that can be used to improve customer support performance, gain insights into customer behavior, and integrate with other systems for a more seamless customer experience.
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.
Taking the customer relationship management (CRM) platform up a notch, Zendesk Sunshine makes it possible for businesses to connect the dots to build the full picture of their customer from data anywhere. Offering much more than the old legacy CRM platform, Zendesk Sunshine takes a new and more modern approach, native to AWS, that provides the tools needed for developers and admins to create superior customer experiences.
Zendesk Sunshine's API provides access to a wide range of data categories, including:
1. Customer data: This includes information about customers such as their name, email address, phone number, and other contact details.
2. Ticket data: This includes information about customer support tickets, such as the status of the ticket, the customer's issue, and any notes or comments added by support agents.
3. Agent data: This includes information about support agents, such as their name, email address, and performance metrics.
4. Analytics data: This includes data about customer support performance, such as response times, ticket volume, and customer satisfaction ratings.
5. Integration data: This includes data about integrations with other systems, such as CRM or marketing automation platforms.
6. Custom data: This includes any custom data fields that have been added to the Zendesk platform, such as customer preferences or product information.
Overall, Zendesk Sunshine's API provides access to a wide range of data that can be used to improve customer support performance, gain insights into customer behavior, and integrate with other systems for a more seamless customer experience.
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.
Taking the customer relationship management (CRM) platform up a notch, Zendesk Sunshine makes it possible for businesses to connect the dots to build the full picture of their customer from data anywhere. Offering much more than the old legacy CRM platform, Zendesk Sunshine takes a new and more modern approach, native to AWS, that provides the tools needed for developers and admins to create superior customer experiences.
Zendesk Sunshine's API provides access to a wide range of data categories, including:
1. Customer data: This includes information about customers such as their name, email address, phone number, and other contact details.
2. Ticket data: This includes information about customer support tickets, such as the status of the ticket, the customer's issue, and any notes or comments added by support agents.
3. Agent data: This includes information about support agents, such as their name, email address, and performance metrics.
4. Analytics data: This includes data about customer support performance, such as response times, ticket volume, and customer satisfaction ratings.
5. Integration data: This includes data about integrations with other systems, such as CRM or marketing automation platforms.
6. Custom data: This includes any custom data fields that have been added to the Zendesk platform, such as customer preferences or product information.
Overall, Zendesk Sunshine's API provides access to a wide range of data that can be used to improve customer support performance, gain insights into customer behavior, and integrate with other systems for a more seamless customer experience.
1. First, navigate to the Zendesk Sunshine source connector page on Airbyte.com.
2. Click on the "Add Source" button to begin the process of adding your Zendesk Sunshine credentials.
3. In the "Connection Configuration" section, enter your Zendesk Sunshine account subdomain and API token.
4. To obtain your API token, log in to your Zendesk Sunshine account and navigate to the "Admin" settings. From there, click on "API" and generate a new token.
5. Once you have entered your subdomain and API token, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save & Continue" button to proceed to the next step.
7. In the "Schema Selection" section, select the data that you want to replicate from your Zendesk Sunshine account.
8. You can choose to replicate all data or select specific tables and columns.
9. Once you have made your selections, click on the "Save & Continue" button to proceed to the final step.
10. In the "Destination Configuration" section, select the destination where you want to replicate your Zendesk Sunshine data.
11. You can choose from a variety of destinations, including databases, data warehouses, and cloud storage services.
12. Once you have selected your destination, click on the "Create Connection" button to complete the process of connecting your Zendesk Sunshine source connector on Airbyte.com.
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.
