The things I like about StreamSets are its * overall user interface * efficiency * product features, which are all good. Also, the scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy. You just need to configure the data sources, the paths and their configurations, and you are ready to go. It is very efficient and very easy to use for ETL pipelines. It is a GUI-based interface in which you can easily create or design your own data pipelines with just a few clicks. As for moving data into modern analytics systems, we are using it with Microsoft Power BI, AWS, and some on-premises solutions, and it is very easy to get data from StreamSets into them. No hardcore coding or special technical expertise is required. It is also a no-code platform in which you can configure your data sources and data output for easy configuration of your data pipeline. This is a very important aspect because if a tool requires code development, we need to hire software developers to get the task done. By using StreamSets, it can be done with a few clicks.
