Hive is built on top of Hadoop, which is based on static batch processing, and which typically has high latency and requires a lot of overhead during job submission and scheduling. As a result, Hive is not able to achieve fast queries with low latency on large-scale datasets; for example, Hive typically executes queries on datasets of a few hundred megabytes with minute latency. As a result,

Hive is not suitable for applications that require low latency, such as online transaction processing (OLTP).The Hive querying process strictly adheres to the Hadoop MapReduce job execution model, where Hive converts a user's HiveQL statement into a MapReduce job via the interpreter and submits it to the Hadoop cluster. Hadoop monitors the job execution process and returns the results to the user. Hive is not designed for online transaction processing, and it does not provide real-time querying or row-level data update operations.