Elastic's blog post discusses the differences between the Watcher and Percolator APIs within the Elastic product stack, focusing on their distinct use cases and functionalities. While both are used for matching documents against queries, Percolator is designed to ascertain which queries a specific document would match in real-time, making it suitable for applications needing immediate alerting on new documents. In contrast, Watcher periodically executes pre-defined queries against a document corpus, allowing for trend analysis and actions based on changes over time, such as monitoring seasonal trends or periodic data checks. The post also touches on the scalability of both tools, explaining that Percolator scales linearly with the number of queries and excels in scenarios with high query cardinality and low document throughput. The Watcher, on the other hand, is advantageous for scenarios that require periodic monitoring and can handle a larger document corpus. The blog also mentions future enhancements to Watcher, including the potential for real-time alerts and integration with Percolator results.