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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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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.
SonarCloud is a service that can be integrated into Azure DevOps via an extension. SonarCloud is a cloud-based solution to analyze code and that have also remaining code quality and security service to catch Security Vulnerabilities, Bugs, and Code. SonarCloud is an application that you can use to build robust and safe applications. One can use SonarCloud as a static analysis tool to analyze the code in the source graph repository for security vulnerabilities.
Amazon S3 (Simple Storage Service) is a cloud-based object storage service provided by Amazon Web Services (AWS). It is designed to store and retrieve any amount of data from anywhere on the web. S3 is highly scalable, secure, and durable, making it an ideal solution for businesses of all sizes. S3 allows users to store and retrieve data in the form of objects, which can be up to 5 terabytes in size. These objects can be accessed through a web interface or through APIs, making it easy to integrate with other AWS services or third-party applications. S3 also offers a range of features, including versioning, lifecycle policies, and access control, which allow users to manage their data effectively. It also provides high availability and durability, ensuring that data is always accessible and protected against data loss. Overall, S3 is a powerful and flexible tool that enables businesses to store and manage their data in a secure and scalable way, making it an essential component of many cloud-based applications and services.
SonarCloud's API provides access to a wide range of data related to software development and code quality. The following are the categories of data that can be accessed through the API:
1. Code Quality Metrics: SonarCloud's API provides access to various code quality metrics such as code coverage, code duplication, code complexity, and code smells.
2. Security Vulnerabilities: The API provides information on security vulnerabilities in the code, including details on the type of vulnerability, its severity, and recommendations for remediation.
3. Technical Debt: The API provides information on technical debt in the code, including the estimated time required to fix the debt and the cost of fixing it.
4. Code Issues: The API provides information on code issues such as bugs, vulnerabilities, and code smells, along with details on their severity and recommendations for remediation.
5. Project and Repository Information: The API provides information on the project and repository, including details on the codebase, the number of lines of code, and the number of contributors.
6. Continuous Integration and Deployment: The API provides information on the status of continuous integration and deployment pipelines, including build and deployment success rates, and the time taken for each step.
Overall, SonarCloud's API provides developers with a comprehensive set of data to help them improve the quality of their code and streamline their development processes.
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.
