Web API Limitations

I think for 15,000 records the queryEntity returns data more than 1 MB and takes more than 10sec, and hence it timesout, which maybe causing an issue.
One solution would be - let the caller of the web api pass a startIndex and batchSize. In your web api you can extract those from the query params. And then you can send only requested amount of data rather than all of it.
The caller can then make another web api call with startIndex = oldStartIndex+batchSize. This will fetch the next batch of records. You will have to decide what batch Size is suitable.
So, in a way you will have multiple webapi calls to get all the data.

If on the other hand you want to get all the data in one-go, you will need to see if you can optimize at database level, maybe use indexes on proper columns, that may help with queryEntity timeout issue.
Another idea could be to return data in aggregate form - maybe create a DB View for the table which has lot of data. The View can aggregate data of multiple rows based on some column, this will reduce the number of rows returned. Then your web api will return less than 15000 rows. But, now the caller of the web api will need to apply some transformation on the data returned to get the exact data (since at DB side we grouped and aggregated the data in the View).

I think for 15,000 records the queryEntity returns data more than 1 MB and takes more than 10sec, and hence it timesout, which maybe causing an issue.
One solution would be - let the caller of the web api pass a startIndex and batchSize. In your web api you can extract those from the query params. And then you can send only requested amount of data rather than all of it.
The caller can then make another web api call with startIndex = oldStartIndex+batchSize. This will fetch the next batch of records. You will have to decide what batch Size is suitable.
So, in a way you will have multiple webapi calls to get all the data.

If on the other hand you want to get all the data in one-go, you will need to see if you can optimize at database level, maybe use indexes on proper columns, that may help with queryEntity timeout issue.
Another idea could be to return data in aggregate form - maybe create a DB View for the table which has lot of data. The View can aggregate data of multiple rows based on some column, this will reduce the number of rows returned. Then your web api will return less than 15000 rows. But, now the caller of the web api will need to apply some transformation on the data returned to get the exact data (since at DB side we grouped and aggregated the data in the View).