When you want to run an UPDATE query(or other DML operations) over a very huge table having over a billion rows or even 100s of Million it is recommended that you should not update them at one go.
Consequently, the overall program running time increases as well.
How can I improve the update performance of this very large My ISAM table?
With Heap SQL, we’re syncing large amounts of data across ~80 Redshift clusters on a daily basis.
At first, the sync process we designed was too slow to be viable for large customers.
Since so many Heap customers use Redshift, we built Heap SQL to allow them to sync their Heap datasets to their own Redshift clusters.