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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.
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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.
Docker Hub is the world's easiest way to create, manage, and deliver your team's container applications. Docker Hub assists developers bring their ideas to life by conquering the complexity of app development. It can easily search more than one million container images, including Certified and community-provided images. Docker Hub gets access to free public repositories or choose a subscription plan for private ropes. It is entirely a trusted way to run more technology in containers with certified infrastructure, containers and plugins.
Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.
Dockerhub's API provides access to a wide range of data related to Docker images and repositories. The following are the categories of data that can be accessed through Dockerhub's API:
1. Repositories: Information about the repositories available on Dockerhub, including their names, descriptions, and tags.
2. Images: Details about the Docker images available on Dockerhub, including their names, tags, and sizes.
3. Users: Information about the users who have created and contributed to the repositories and images on Dockerhub.
4. Organizations: Details about the organizations that have created and contributed to the repositories and images on Dockerhub.
5. Webhooks: Information about the webhooks that have been set up for repositories and images on Dockerhub.
6. Builds: Details about the builds that have been performed on Dockerhub, including their status and logs.
7. Collaborators: Information about the collaborators who have access to the repositories and images on Dockerhub.
8. Permissions: Details about the permissions that have been set for repositories and images on Dockerhub, including read, write, and admin access.
Overall, Dockerhub's API provides a comprehensive set of data that can be used to manage and monitor Docker images and repositories.
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.
