Younium streamlines subscription management, automates billing, and provides analytics for SaaS businesses, enhancing efficiency and revenue tracking. Ideal for scaling operations.
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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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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
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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.
Younium is the subscription management and billing platform for B2B SaaS that includes Subscription Management, Subscription Billing, Payments, invoicing/billing, financial reporting. Younium page contains the reference information and setup guide for this source connector. Younium symbolizes a Geometric Lowercase Sans-Serif Letter Y logo. Younium carries the transformative infrastructure to manage and improve your business. There have an active Technology Partnership between Younium and Visma remaining 205 partners and share 3 partners.
Younium's API provides access to a wide range of data related to energy consumption and production. The following are the categories of data that can be accessed through Younium's API:
1. Energy consumption data: This includes data related to the amount of energy consumed by a building or facility over a specific period of time.
2. Energy production data: This includes data related to the amount of energy produced by renewable energy sources such as solar panels or wind turbines.
3. Weather data: This includes data related to weather conditions such as temperature, humidity, and wind speed, which can impact energy consumption and production.
4. Building data: This includes data related to the physical characteristics of a building such as its size, layout, and construction materials.
5. Occupancy data: This includes data related to the number of people occupying a building or facility, which can impact energy consumption.
6. Equipment data: This includes data related to the energy consumption of specific equipment such as HVAC systems, lighting, and appliances.
7. Cost data: This includes data related to the cost of energy consumption and production, which can be used to optimize energy usage and reduce costs.
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.
Younium is the subscription management and billing platform for B2B SaaS that includes Subscription Management, Subscription Billing, Payments, invoicing/billing, financial reporting. Younium page contains the reference information and setup guide for this source connector. Younium symbolizes a Geometric Lowercase Sans-Serif Letter Y logo. Younium carries the transformative infrastructure to manage and improve your business. There have an active Technology Partnership between Younium and Visma remaining 205 partners and share 3 partners.
Younium's API provides access to a wide range of data related to energy consumption and production. The following are the categories of data that can be accessed through Younium's API:
1. Energy consumption data: This includes data related to the amount of energy consumed by a building or facility over a specific period of time.
2. Energy production data: This includes data related to the amount of energy produced by renewable energy sources such as solar panels or wind turbines.
3. Weather data: This includes data related to weather conditions such as temperature, humidity, and wind speed, which can impact energy consumption and production.
4. Building data: This includes data related to the physical characteristics of a building such as its size, layout, and construction materials.
5. Occupancy data: This includes data related to the number of people occupying a building or facility, which can impact energy consumption.
6. Equipment data: This includes data related to the energy consumption of specific equipment such as HVAC systems, lighting, and appliances.
7. Cost data: This includes data related to the cost of energy consumption and production, which can be used to optimize energy usage and reduce costs.
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.
Younium is the subscription management and billing platform for B2B SaaS that includes Subscription Management, Subscription Billing, Payments, invoicing/billing, financial reporting. Younium page contains the reference information and setup guide for this source connector. Younium symbolizes a Geometric Lowercase Sans-Serif Letter Y logo. Younium carries the transformative infrastructure to manage and improve your business. There have an active Technology Partnership between Younium and Visma remaining 205 partners and share 3 partners.
Younium's API provides access to a wide range of data related to energy consumption and production. The following are the categories of data that can be accessed through Younium's API:
1. Energy consumption data: This includes data related to the amount of energy consumed by a building or facility over a specific period of time.
2. Energy production data: This includes data related to the amount of energy produced by renewable energy sources such as solar panels or wind turbines.
3. Weather data: This includes data related to weather conditions such as temperature, humidity, and wind speed, which can impact energy consumption and production.
4. Building data: This includes data related to the physical characteristics of a building such as its size, layout, and construction materials.
5. Occupancy data: This includes data related to the number of people occupying a building or facility, which can impact energy consumption.
6. Equipment data: This includes data related to the energy consumption of specific equipment such as HVAC systems, lighting, and appliances.
7. Cost data: This includes data related to the cost of energy consumption and production, which can be used to optimize energy usage and reduce costs.
1. First, navigate to the Younium source connector page on Airbyte.com.
2. Click on the "Create a new connection" button.
3. Enter a name for your connection and click "Next".
4. In the "Configure your Younium connection" section, enter your Younium API key and API secret.
5. Click "Test connection" to ensure that the credentials are correct and the connection is successful.
6. Once the connection is successful, select the tables you want to replicate from Younium to Airbyte.
7. Click "Next" and configure any additional settings for your connection, such as scheduling and data syncing options.
8. Click "Create connection" to finalize the setup of your Younium source connector on Airbyte.com.
9. You can now view and manage your Younium connection from the Airbyte dashboard.
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.