Connect Adobe Stock and Zilliz to Build Intelligent Automations
Enable Integrations or automations with these events of Adobe Stock and Zilliz
Enable Integrations or automations with these events of Adobe Stock and Zilliz
Actions
Search Image
Search an Image using keyword
Get Caterogy
Get top categories of adobe stock
List Clusters
List all the Cluster
List Cloud Regions
List all the Cloud regions in zilliz.
Create Cluster
Create a dedicated cluster.
Delete Cluster
Deletes a Specified Cluster
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Frequently Asked Questions
To start, connect both your Adobe Stock and Zilliz accounts to viaSocket. Once connected, you can set up a workflow where an event in Adobe Stock triggers actions in Zilliz (or vice versa).
Absolutely. You can customize how Adobe Stock data is recorded in Zilliz. This includes choosing which data fields go into which fields of Zilliz, setting up custom formats, and filtering out unwanted information.
The data sync between Adobe Stock and Zilliz typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Adobe Stock and Zilliz. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Adobe Stock
Adobe Stock is a stock media service offering high-quality, royalty-free assets like photos, videos, and illustrations, integrated with Adobe Creative Cloud. It provides flexible licensing options, allowing users to easily access and license assets for creative projects.
Learn MoreAbout Zilliz
Zilliz is a leading provider of vector database solutions, designed to handle large-scale data processing and analytics. It offers advanced capabilities for managing and querying vector data, making it ideal for AI and machine learning applications. Zilliz's platform is optimized for high performance and scalability, enabling businesses to efficiently process and analyze complex datasets.
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