Gridly is a collaborative content management platform that streamlines localization, version control, and real-time editing, enhancing efficiency for game developers and global teams.
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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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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.
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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.
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.
Gridly is a cloud-based headless CMS for multilingual game-as-a-service projects with an open API, browser-based spreadsheet UI, and built-in functions to handle localization and frequent updates. It is a collaborative system for users of any technical ability. Gridly is spreadsheet for multi-language content tailor-made for games and digital products. By connecting development, design, and localization teams and their tools, Gridly serves as a single source of truth for faster content updates. Gridly improves collaboration and streamlines content management and localization for your games or apps.
Gridly's API provides access to various types of data that can be used to manage and organize content for web and mobile applications. The following are the categories of data that Gridly's API gives access to:
1. Content data: This includes all the content that is stored in Gridly, such as text, images, videos, and audio files.
2. Metadata: This includes information about the content, such as the date it was created, the author, and any tags or categories associated with it.
3. User data: This includes information about the users who access the content, such as their login credentials, preferences, and activity history.
4. Analytics data: This includes data about how users interact with the content, such as page views, clicks, and engagement metrics.
5. Configuration data: This includes settings and configurations for the application, such as user permissions, access controls, and integration with other systems.
Overall, Gridly's API provides a comprehensive set of data that can be used to build and manage content-rich 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.
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.
Gridly is a cloud-based headless CMS for multilingual game-as-a-service projects with an open API, browser-based spreadsheet UI, and built-in functions to handle localization and frequent updates. It is a collaborative system for users of any technical ability. Gridly is spreadsheet for multi-language content tailor-made for games and digital products. By connecting development, design, and localization teams and their tools, Gridly serves as a single source of truth for faster content updates. Gridly improves collaboration and streamlines content management and localization for your games or apps.
Gridly's API provides access to various types of data that can be used to manage and organize content for web and mobile applications. The following are the categories of data that Gridly's API gives access to:
1. Content data: This includes all the content that is stored in Gridly, such as text, images, videos, and audio files.
2. Metadata: This includes information about the content, such as the date it was created, the author, and any tags or categories associated with it.
3. User data: This includes information about the users who access the content, such as their login credentials, preferences, and activity history.
4. Analytics data: This includes data about how users interact with the content, such as page views, clicks, and engagement metrics.
5. Configuration data: This includes settings and configurations for the application, such as user permissions, access controls, and integration with other systems.
Overall, Gridly's API provides a comprehensive set of data that can be used to build and manage content-rich 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.
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.
Gridly is a cloud-based headless CMS for multilingual game-as-a-service projects with an open API, browser-based spreadsheet UI, and built-in functions to handle localization and frequent updates. It is a collaborative system for users of any technical ability. Gridly is spreadsheet for multi-language content tailor-made for games and digital products. By connecting development, design, and localization teams and their tools, Gridly serves as a single source of truth for faster content updates. Gridly improves collaboration and streamlines content management and localization for your games or apps.
Gridly's API provides access to various types of data that can be used to manage and organize content for web and mobile applications. The following are the categories of data that Gridly's API gives access to:
1. Content data: This includes all the content that is stored in Gridly, such as text, images, videos, and audio files.
2. Metadata: This includes information about the content, such as the date it was created, the author, and any tags or categories associated with it.
3. User data: This includes information about the users who access the content, such as their login credentials, preferences, and activity history.
4. Analytics data: This includes data about how users interact with the content, such as page views, clicks, and engagement metrics.
5. Configuration data: This includes settings and configurations for the application, such as user permissions, access controls, and integration with other systems.
Overall, Gridly's API provides a comprehensive set of data that can be used to build and manage content-rich applications.
1. First, navigate to the Gridly source connector page on Airbyte.com.
2. Click on the "Create new connection" button.
3. In the "Configuration" tab, enter a name for your connection.
4. In the "Source" section, select "Gridly" from the dropdown menu.
5. In the "API Key" field, enter your Gridly API key.
6. In the "Project ID" field, enter the ID of the Gridly project you want to connect to.
7. In the "Schema" section, select the schema you want to use for your data.
8. In the "Tables" section, select the tables you want to include in your data sync.
9. Click on the "Test" button to ensure that your connection is working properly.
10. If the test is successful, click on the "Create connection" button to save your configuration.
11. You can now use your Gridly source connector to sync data with your destination of choice.
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.