When using SQL HEAP, the entire dataset is loaded into memory, which can be beneficial for small to medium-sized datasets that can fit within the available RAM. However, if the dataset size exceeds the available memory, or if the memory is being utilized by other processes, it is possible to run out of memory.

Running out of memory can lead to various issues such as slow performance, crashes, or inability to execute queries. To mitigate this, it is important to monitor the memory usage and make sure the dataset is within the available memory capacity.

When dealing with large datasets that cannot fit entirely in memory, alternative solutions such as disk-based databases or distributed computing systems may be more suitable. These solutions allow for efficient data storage and processing, even when the dataset size exceeds the available memory.

Overall, while SQL HEAP can provide performance advantages by utilizing in-memory storage, it is important to be mindful of the available memory capacity to prevent running out of memory.