Everhour is a time tracking and project management tool that integrates with popular platforms like Asana, Trello, and Jira, enhancing productivity and enabling precise billing and budgeting.
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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
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- Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.
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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.
Everhour is a time tracking and project management tool that helps businesses and teams to manage their time more efficiently. It integrates with popular project management tools like Asana, Trello, and Basecamp, allowing users to track time spent on tasks and projects directly from those platforms. Everhour also offers features like budget tracking, invoicing, and reporting, giving businesses a comprehensive view of their time and project management. With Everhour, teams can easily collaborate, manage their workload, and stay on top of deadlines, ultimately improving productivity and profitability.
Everhour's API provides access to a wide range of data related to time tracking and project management. The following are the categories of data that can be accessed through Everhour's API:
1. Time tracking data: This includes data related to the time spent on tasks, projects, and clients.
2. Project management data: This includes data related to projects, tasks, and subtasks, such as their status, due dates, and assignees.
3. User data: This includes data related to users, such as their name, email address, and role.
4. Billing data: This includes data related to billing, such as the amount billed, the currency used, and the payment status.
5. Reporting data: This includes data related to reports, such as the type of report, the date range, and the data included in the report.
6. Integration data: This includes data related to integrations with other tools, such as the name of the integration, the status, and the configuration settings.
Overall, Everhour's API provides a comprehensive set of data that can be used to track time, manage projects, and analyze performance.
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.
Everhour is a time tracking and project management tool that helps businesses and teams to manage their time more efficiently. It integrates with popular project management tools like Asana, Trello, and Basecamp, allowing users to track time spent on tasks and projects directly from those platforms. Everhour also offers features like budget tracking, invoicing, and reporting, giving businesses a comprehensive view of their time and project management. With Everhour, teams can easily collaborate, manage their workload, and stay on top of deadlines, ultimately improving productivity and profitability.
Everhour's API provides access to a wide range of data related to time tracking and project management. The following are the categories of data that can be accessed through Everhour's API:
1. Time tracking data: This includes data related to the time spent on tasks, projects, and clients.
2. Project management data: This includes data related to projects, tasks, and subtasks, such as their status, due dates, and assignees.
3. User data: This includes data related to users, such as their name, email address, and role.
4. Billing data: This includes data related to billing, such as the amount billed, the currency used, and the payment status.
5. Reporting data: This includes data related to reports, such as the type of report, the date range, and the data included in the report.
6. Integration data: This includes data related to integrations with other tools, such as the name of the integration, the status, and the configuration settings.
Overall, Everhour's API provides a comprehensive set of data that can be used to track time, manage projects, and analyze performance.
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.
Everhour is a time tracking and project management tool that helps businesses and teams to manage their time more efficiently. It integrates with popular project management tools like Asana, Trello, and Basecamp, allowing users to track time spent on tasks and projects directly from those platforms. Everhour also offers features like budget tracking, invoicing, and reporting, giving businesses a comprehensive view of their time and project management. With Everhour, teams can easily collaborate, manage their workload, and stay on top of deadlines, ultimately improving productivity and profitability.
Everhour's API provides access to a wide range of data related to time tracking and project management. The following are the categories of data that can be accessed through Everhour's API:
1. Time tracking data: This includes data related to the time spent on tasks, projects, and clients.
2. Project management data: This includes data related to projects, tasks, and subtasks, such as their status, due dates, and assignees.
3. User data: This includes data related to users, such as their name, email address, and role.
4. Billing data: This includes data related to billing, such as the amount billed, the currency used, and the payment status.
5. Reporting data: This includes data related to reports, such as the type of report, the date range, and the data included in the report.
6. Integration data: This includes data related to integrations with other tools, such as the name of the integration, the status, and the configuration settings.
Overall, Everhour's API provides a comprehensive set of data that can be used to track time, manage projects, and analyze performance.
1. First, log in to your Everhour account and navigate to the API Access page.
2. Generate a new API key by clicking on the ""Generate new API key"" button.
3. Copy the API key to your clipboard.
4. Open the Airbyte platform and navigate to the ""Sources"" tab.
5. Click on the ""New Source"" button and select ""Everhour"" from the list of available connectors.
6. Enter a name for your Everhour source connector and paste the API key you copied earlier into the appropriate field.
7. Click on the ""Test"" button to ensure that the connection is successful.
8. If the test is successful, click on the ""Create"" button to save your Everhour source connector.
9. You can now use your Everhour source connector to extract data from your Everhour account and integrate it with other tools and platforms.
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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