Search Enhancement Features for OpenSearch Clusters

Compared with open-source OpenSearch, OpenSearch clusters in CSS have many enhanced features. Table 1 lists these enhanced features and the corresponding cluster versions.

**Table 1** Search enhancement features for OpenSearch clusters
Enhanced Feature	Description	Cluster Version	Details
Vector search	Unstructured data, such as images, videos, and language corpora, is converted into vectors, which are searched based on similarity using either an exact or approximate nearest neighbors algorithm.	OpenSearch 1.3.6	About Vector Search
Storage-compute decoupling	CSS stores new data as hot data on SSDs to ensure optimal query performance, and historical data as cold data in OBS to cut storage costs. Compared with cold/hot storage switchover, storage-compute decoupling is a better option for use cases that are not particularly demanding in terms of search performance, as cold data is stored in OBS, which cuts storage costs.	OpenSearch 1.3.6	Configuring Storage-Compute Decoupling for an OpenSearch Cluster
Switchover between hot and cold storage	You can keep hot data on high-performance servers to ensure fast query response times (in seconds). For historical data that requires a query response time of minutes, you can keep it on large-capacity, low-specs servers as cold data. This allows you to cut storage costs and improve search efficiency. Compared with storage-compute decoupling, cold/hot storage switchover is a better option for use cases that are demanding in terms of search performance. Cold data is stored on local cold data nodes in the cluster. The storage capacity available depends on the number of cold data nodes and their disk capacity. The storage cost is higher than that of OBS.	This feature is supported as long as the cluster has cold data nodes.	Switching Between Hot and Cold Storage for an OpenSearch Cluster