* Microsoft SSIS is still there, kind of a granddaddy tool but perfectly capable of single-machine ETL
* Trifacta's Wrangler has a free version with limits
* Talend's Open Studio is free, a little clunky but works fine
* Some new players that I've played around with are Airbyte (immature but evolving quick) and Fivetran (consumption-based pricing model, fairly extensible, but kind of biased about the sources/sinks they're interested in supporting)
* I haven't tried Streamsets or Stitch yet, but I've watched a few videos, again, a little more focused on cloud and streaming data sources than traditional batch ETL, but seem fair enough for those use cases as well
* If you want to roll your own SQL/Python/etc ETL, Airflow and Luigi are good and simple orchestrators/schedulers
The cloud services have pretty cheap consumption-based ETL PaaS offerings, too: Azure Data Factory, Amazon Glue, GCP Cloud Data Fusion
Unless what you're doing is highly bespoke ETL, I'd recommend trying out the new kids on the block and seeing if you can build pipelines that suit your needs from those, because they're at the forefront of a lot of evolving data architecture patterns that are about to dominate the 2020s.
* Microsoft SSIS is still there, kind of a granddaddy tool but perfectly capable of single-machine ETL
* Trifacta's Wrangler has a free version with limits
* Talend's Open Studio is free, a little clunky but works fine
* Some new players that I've played around with are Airbyte (immature but evolving quick) and Fivetran (consumption-based pricing model, fairly extensible, but kind of biased about the sources/sinks they're interested in supporting)
* I haven't tried Streamsets or Stitch yet, but I've watched a few videos, again, a little more focused on cloud and streaming data sources than traditional batch ETL, but seem fair enough for those use cases as well
* If you want to roll your own SQL/Python/etc ETL, Airflow and Luigi are good and simple orchestrators/schedulers
The cloud services have pretty cheap consumption-based ETL PaaS offerings, too: Azure Data Factory, Amazon Glue, GCP Cloud Data Fusion
Unless what you're doing is highly bespoke ETL, I'd recommend trying out the new kids on the block and seeing if you can build pipelines that suit your needs from those, because they're at the forefront of a lot of evolving data architecture patterns that are about to dominate the 2020s.