Change Data Capture Into a Runtime: One Pipeline for Pages, Search, and AI Agents

Harper emerges as a versatile runtime solution capable of handling both payload and trigger-based change data capture (CDC) events, offering a distinct advantage over traditional data destinations like data warehouses, message queues, and CDN caches, which typically struggle with trigger events. Unlike these systems, Harper allows data to be queried and updated in real-time, efficiently supporting complex workflows such as re-rendering pages or updating AI agent contexts with minimal latency. This unique capability is illustrated by a top US department store's implementation, where Harper processes product change events, enabling rapid page updates directly tied to these changes. Harper's architecture allows it to serve as both a destination and a potential future source of truth, with its native replication feature ensuring data consistency across regions. This positions Harper as a robust solution for modern applications requiring immediate and dynamic data handling, particularly in environments with large catalogs and diverse consumer demands.

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