The features that I find most valuable within Microsoft Azure Cosmos DB are probably the cost, as the cost optimization is good. The storage and queryability are good for what we're doing; it's a lot of unstructured data, so having a platform to put that in and then be able to harvest that data out for the reporting we do is essential. In terms of cost saving, it was probably easily 30 to 40% cheaper than doing a standard SQL, which is what we saw just on piloting and getting in there. We were initially thinking 20 to 25%, but we were probably more at the 35 to 40%. We are using Microsoft Azure Cosmos DB's hybrid search today. The value that it has added to my AI or search workloads is that I think it's optimized that process and made it easier. We have a lot of unstructured data coming from different dissimilar systems and different data sources, so correlating those things together and making sense of it has been very beneficial. Microsoft Azure Cosmos DB has had pretty good performance with searching through large amounts of data; it's been fast, and we haven't seen a lot of performance degradation while building larger queries and bringing in a large set of data. The dynamic auto-scale or serverless model from Microsoft Azure Cosmos DB has helped reduce costs and operational effort; however, it's hard to quantify how that plays out since you're using a shared service. It shifts my focus away from building, managing, and upgrading to adding value.
