Couchbase 7.2 introduces a new time-series feature that enhances the storage and analysis of time-series data by building on the existing Couchbase distributed database architecture, known for its scalability, redundancy, and high availability. The feature leverages Couchbase SQL++ and SDKs for efficient data handling, allowing users to store large volumes of time-stamped data points in JSON documents, optimizing both storage and retrieval processes. Key benefits include efficient storage, advanced query capabilities, and low index storage requirements, all of which support complex analytical use cases such as financial trading, IoT monitoring, and predictive maintenance. The time-series data is stored using arrays, reducing the number of documents needed and enhancing database performance, while epoch time is employed over ISO date strings to minimize data size and improve processing speed. Couchbase's time-series functionality includes a new _timeseries function for optimized querying and supports advanced analytics through SQL++ capabilities, enabling users to perform tasks like calculating moving averages and generating buy/sell signals based on Relative Strength Index analysis. The feature is designed to integrate seamlessly with existing infrastructures, allowing for effortless expansion as data needs grow, and it encourages efficient data ingestion strategies by enabling flexible data point storage within JSON arrays.