Pingdom monitors website performance and uptime, providing real-time alerts and detailed reports. It's essential for ensuring optimal user experience and quick issue resolution.
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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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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.
1. Website uptime and downtime: Pingdom's API allows you to extract data on the uptime and downtime of your website. This includes the duration of each outage and the time of occurrence.
2. Response time: You can also extract data on the response time of your website. This includes the time it takes for your website to load and respond to user requests.
3. Performance metrics: Pingdom's API provides data on various performance metrics such as page size, load time, and number of requests. This data can help you identify areas for improvement in your website's performance.
4. Server performance: You can also extract data on your server's performance, including CPU usage, memory usage, and disk space.
5. Alert notifications: Pingdom's API allows you to extract data on alert notifications, including the type of alert, the time it was triggered, and the recipient of the alert.
6. Historical data: You can also extract historical data on your website's performance, including uptime, response time, and performance metrics. This data can help you identify trends and patterns over time.
7. Real-time monitoring: Pingdom's API provides real-time monitoring data, allowing you to track your website's performance in real-time and respond to issues as they occur.
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. Website uptime and downtime: Pingdom's API allows you to extract data on the uptime and downtime of your website. This includes the duration of each outage and the time of occurrence.
2. Response time: You can also extract data on the response time of your website. This includes the time it takes for your website to load and respond to user requests.
3. Performance metrics: Pingdom's API provides data on various performance metrics such as page size, load time, and number of requests. This data can help you identify areas for improvement in your website's performance.
4. Server performance: You can also extract data on your server's performance, including CPU usage, memory usage, and disk space.
5. Alert notifications: Pingdom's API allows you to extract data on alert notifications, including the type of alert, the time it was triggered, and the recipient of the alert.
6. Historical data: You can also extract historical data on your website's performance, including uptime, response time, and performance metrics. This data can help you identify trends and patterns over time.
7. Real-time monitoring: Pingdom's API provides real-time monitoring data, allowing you to track your website's performance in real-time and respond to issues as they occur.
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. Website uptime and downtime: Pingdom's API allows you to extract data on the uptime and downtime of your website. This includes the duration of each outage and the time of occurrence.
2. Response time: You can also extract data on the response time of your website. This includes the time it takes for your website to load and respond to user requests.
3. Performance metrics: Pingdom's API provides data on various performance metrics such as page size, load time, and number of requests. This data can help you identify areas for improvement in your website's performance.
4. Server performance: You can also extract data on your server's performance, including CPU usage, memory usage, and disk space.
5. Alert notifications: Pingdom's API allows you to extract data on alert notifications, including the type of alert, the time it was triggered, and the recipient of the alert.
6. Historical data: You can also extract historical data on your website's performance, including uptime, response time, and performance metrics. This data can help you identify trends and patterns over time.
7. Real-time monitoring: Pingdom's API provides real-time monitoring data, allowing you to track your website's performance in real-time and respond to issues as they occur.
1. Open the Pingdom source connector page on Airbyte.
2. Click on the "Create new connection" button.
3. Enter a name for your connection.
4. Enter your Pingdom API token in the "API Token" field.
5. Enter your Pingdom username in the "Username" field.
6. Enter your Pingdom password in the "Password" field.
7. Click on the "Test" button to verify your credentials.
8. If the test is successful, click on the "Save & Continue" button.
9. Select the Pingdom data you want to replicate. 10. Click on the "Save & Sync" button to start replicating your data.
Note: The Pingdom source connector on Airbyte allows you to replicate data from your Pingdom account, such as uptime and performance metrics, into your data warehouse or other destination. The API token is required to authenticate your connection and access your Pingdom 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.
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