I am going for NNY.
This brings back memories from over a decade ago, when M$ used to put hard numbers on their definitions for OLTP: 70% writes and 30% reads.
Following your logic, then it should be YYY because we do insert a shitload of data into OLAP (TB-sized data). But it doesn't mean it is optimized for writes.
Agree !
Ref: https://learn.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-analytical-processing
"Semantic modeling is predominately used for read-heavy scenarios, such as analytics and business intelligence (OLAP), as opposed to more write-heavy transactional data processing (OLTP)"
OLTP relies on a database system where data storage is optimized for both read and write operations = TRUE
Online Transaction Processing (OLTP) systems are designed to handle a large number of short online transactions (insert, update, delete). Therefore, they require a database system optimized for both read and write operations to ensure high efficiency and quick response times. These systems are used in environments where data consistency, speed, and reliability of transaction processing are critical, such as in banking, order entry, and retail sales.
if we compare OLAP and OLTP when say "optimized for reads" then I want to say no, although by itself OLTP is intended to read transactions data and it should be quite good because there are indexes, problems start when complex joins come. It resembles comparing a compact car and E class, both are optimized for driving but the kind of driving is different a lot.
Personally, I bet on YNY
NNY
OLTP: Highly normalized tables; very efficient for writes (different tables contain DISTINCT data); less efficient for reads (to aggregate data from highly normalized tables would require TABLE JOINS).
OLAP: Highly aggregated data; less normalized; very efficient for reads (fewer tables with likely DUPLICATE data); less efficient for writes (because data is not normalized).
The answer should be YNY
OLTP is for relational database where we do both type(read/write) of operations.
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