Andy Brownsword has some advice:
Last time out we started to look at optimising SSIS packages by showing how to identify bottlenecks with a handy script. This time we’re turning insights into action to solve those pain points.
The solutions are grouped into 3 areas: Data Flows, as they do a lot of heavy lifting; the Execute SQL task, which can also be used for transformation and calculations; and finally everything else (because the first two are usually the issue).
Andy has some good advice and plenty of links to prior content around optimizing SSIS performance. One small thing I’d add is architectural: think about whether you can solve the slow part inside SQL Server. If you’re grabbing a huge amount of data from a SQL Server instance and then narrowing it down with filters, it might be a lot faster to transform that into a SQL query with a stronger WHERE clause. But let’s say there’s some small file you’re using to filter, so you need to pull all of the data out of SQL Server to compare against the small file so that you know what you need. Instead of pulling all of the data out of SQL Server or setting up a Lookup component to hit the SQL Server instance for each row in the file, how about loading that file into SQL Server and then writing a query to do the work?
In short, the database engine is typically going to be a much better at performance than an integration layer would be.