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We use Azure cognitive search in one of our applications as a read model, I december 2024 we thought of upgrading ourselves from traditional Azure cognitive search to now named a Azure AI search and created a new basic tier service.
Right now in Old azure coginitve search we have approx 5M of documents which takes around 6GB of total storage as shown in image below. Below are the specifications of the same:
Created in 2021 tentative
Tier : Standard
Replicas : 3
Partitions: 1
Total Documents: ~5M
Storage occupied: 6GB
Upon moving to new AI search we rebuilt the indexes with the same ARM template and function that is responsible for creating documents for old one as shown in image below. Below are the observations after creation
Created in December end 2024
Tier: Basic
Replicas: 3
Partitions: 1
Total Documents: ~5M(Same documents as in old version with some additional documents as its in use now)
Storage: ~11GB
Question:
Why is there so much of a difference between these two in terms of storage?
What`s new in AI search that needs more space?
What can be done to reduce the space issue?
The text was updated successfully, but these errors were encountered:
We use Azure cognitive search in one of our applications as a read model, I december 2024 we thought of upgrading ourselves from traditional Azure cognitive search to now named a Azure AI search and created a new basic tier service.
Right now in Old azure coginitve search we have approx 5M of documents which takes around 6GB of total storage as shown in image below. Below are the specifications of the same:
Upon moving to new AI search we rebuilt the indexes with the same ARM template and function that is responsible for creating documents for old one as shown in image below. Below are the observations after creation
Question:
The text was updated successfully, but these errors were encountered: