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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.
Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.
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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.
The intruder is an online vulnerability scanner that finds cyber security weaknesses in your digital infrastructure, to avoid costly data breaches. The intruder was founded in 2015 to help solve the information overload crisis in vulnerability management. Having worked both as an ethical hacker for tier one companies, and for blue teams defending critical national infrastructure, That while vulnerability management tools were great at finding issues, they were less useful when it came to prioritizing them, tracking them, and timely alerting when problems arose.
RabbitMQ is an open-source message broker software that enables communication between different applications and systems. It acts as a mediator between the sender and receiver of messages, ensuring that messages are delivered reliably and efficiently. RabbitMQ uses a messaging protocol called Advanced Message Queuing Protocol (AMQP) to facilitate communication between different applications. It supports multiple messaging patterns such as point-to-point, publish-subscribe, and request-reply. RabbitMQ is highly scalable and can handle large volumes of messages, making it a popular choice for enterprise-level applications. It also provides features such as message routing, message persistence, and message acknowledgments to ensure reliable message delivery.
Intruder's API provides access to a wide range of data related to security testing and vulnerability management. The following are the categories of data that can be accessed through Intruder's API:
1. Vulnerability data: This includes information about the vulnerabilities detected during the security testing process, such as the severity level, description, and recommended remediation steps.
2. Scan data: This includes information about the scans performed, such as the start and end time, scan type, and scan results.
3. Asset data: This includes information about the assets being scanned, such as the IP address, hostname, and operating system.
4. User data: This includes information about the users who have access to the Intruder platform, such as their email address, name, and role.
5. Report data: This includes information about the reports generated by the Intruder platform, such as the report type, format, and content.
6. Integration data: This includes information about the integrations with other tools and platforms, such as the API keys, webhook URLs, and authentication credentials.
Overall, Intruder's API provides a comprehensive set of data that can be used to improve security testing and vulnerability management 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.
