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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
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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
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Why choose Airbyte as the backbone of your data infrastructure?
Keep your data engineering costs in check
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- 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.
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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.
Datadog is a monitoring and analytics tool for information technology (IT) and DevOps teams that can be used for performance metrics as well as event monitoring for infrastructure and cloud services. The software can monitor services such as servers, databases and appliances Datadog monitoring software is available for on-premises deployment or as Software as a Service (SaaS). Datadog supports Windows, Linux and Mac operating systems. Support for cloud service providers includes AWS, Microsoft Azure, Red Hat OpenShift, and Google Cloud Platform.
Microsoft Power BI is a business analytics tool that allows users to visualize and analyze data from various sources. It is a cloud-based service that provides interactive dashboards, reports, and data visualizations that can be shared across an organization. Power BI can connect to a wide range of data sources, including Excel spreadsheets, cloud-based and on-premises data sources, and third-party applications. With Power BI, users can create custom dashboards and reports that provide insights into their business data. The tool offers a range of visualization options, including charts, graphs, and maps, that can be customized to suit specific needs. Users can also create interactive reports that allow them to drill down into their data and explore it in more detail. Power BI also includes features for data modeling and data preparation, allowing users to clean and transform their data before visualizing it. The tool also includes machine learning capabilities that can be used to create predictive models and identify trends in data. Overall, Microsoft Power BI is a powerful tool for businesses looking to gain insights into their data and make data-driven decisions.
Datadog's API provides access to a wide range of data related to monitoring and analytics of IT infrastructure and applications. The following are the categories of data that can be accessed through Datadog's API:
1. Metrics: Datadog's API provides access to a vast collection of metrics related to system performance, network traffic, application performance, and more.
2. Logs: The API allows users to retrieve logs generated by various applications and systems, which can be used for troubleshooting and analysis.
3. Traces: Datadog's API provides access to distributed traces, which can be used to identify performance bottlenecks and optimize application performance.
4. Events: The API allows users to retrieve events generated by various systems and applications, which can be used for alerting and monitoring purposes.
5. Dashboards: Users can retrieve and manage dashboards created in Datadog, which can be used to visualize and analyze data from various sources.
6. Monitors: The API allows users to create, update, and manage monitors, which can be used to alert on specific conditions or events.
7. Synthetic tests: Datadog's API provides access to synthetic tests, which can be used to simulate user interactions with applications and systems to identify performance issues.
Overall, Datadog's API provides a comprehensive set of data that can be used to monitor and optimize IT infrastructure and applications.
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.
