105 IBM StreamSets Reviews
I really like how user friendly IBM StreamSets is, especially the drag and drop interface for designing data pipelines. It makes the process much easier without needing to write complex code. The platform supports both real-time and batch processing, and it has a wide range of connectors, which helped me integrate different data sources without much hassle. I also appreciated the built-in monitoring tools that helped me keep an eye on data flows and troubleshoot issues quickly. Review collected by and hosted on G2.com.
One downside I experienced was performance lag when handling large volumes of data it wasn’t always as fast as I needed. The error logs were sometimes difficult to interpret, especially for more complex issues. Also, while basic tasks were easy to manage, getting into advanced configurations took more time than I expected, and the documentation didn’t always provide clear guidance. Support response times could also be slow when I needed urgent help. Review collected by and hosted on G2.com.
The best thing is how simple it is to use. You don’t need to write much code and the drag and drop makes things fast. It connects to lots of sources which is helpful. Also the monitoring tools are good and helps when things go wrong. Review collected by and hosted on G2.com.
It can get slow when dealing with big amount of data or when you add many steps. The docs are sometimes confusing or missing stuff. Support takes time to respond sometimes and the price is a bit much for smaller teams. Review collected by and hosted on G2.com.
I like IBM StreamSets for its easy-to-use visual interface, real-time data handling, and strong integration with various cloud and on-premise systems. Review collected by and hosted on G2.com.
While IBM StreamSets is powerful, it can sometimes be complex to troubleshoot issues in large pipelines, and performance tuning may require additional effort for very high-volume data loads. Review collected by and hosted on G2.com.
I like how it makes easy in the use-cases of AI, where you can do the continuous training process. Review collected by and hosted on G2.com.
I don't fee that there are any such. Have to use in-order to know. Review collected by and hosted on G2.com.
I like IBM StreamSets ease of use and Customer Support Team. Review collected by and hosted on G2.com.
Almost everything is good. Number of interactive features can be improved. Review collected by and hosted on G2.com.
Listed are the things which I liked most about Streamset -
a. Presence of inbuilt connectors (in-preise version) which can useful in using it for almost every source/target systems.
b. The is GUI is user friendly and it has certainly helped my platform team to create the streaming data pipeline faster )Previously we were using pyspark)
c. Alongwith tool, the Streamset support team is also excellent.
d. The availability of streamsets academy through which we an get our resources trained easily. Review collected by and hosted on G2.com.
There are lesser number of connectors available in the cloud version of Streamsets.
The inability to supports "exactly once" delivery of data creates limitation in few of the use cases.Although we have managed this through workaround but having ths ability in Streamsets will certainly help. Review collected by and hosted on G2.com.
UI of the tool is very easy to understand even for a beginner. It has the graphical pipeline feature to convert source data and add some processing steps on top it and then send it to target system. It seems simple to implement from a docker image in your environment. Opening the tool in your chrome or any web browser is less heavy in terms of RAM usage and logging in and log out times are quick. Review collected by and hosted on G2.com.
It still seems a bit under matured in terms of support for more 3rd party vendors like SAP, Salesforce, etc. Review collected by and hosted on G2.com.
I love the StreamSets UI and its interface. The components in StreamSets are very useful and very easy to use. You can esily implement a pipeline using the desired origin from the lits of various origins. You can use it on daily basis for your pipeline review. The customer support from the StreamSets side is very appreciated. Review collected by and hosted on G2.com.
There is nothing to say bad about it. Just sometimes the preview field lacks in previeing the high intensity data. Review collected by and hosted on G2.com.
I used StreamSets in one of my ETL project where we were working on Apache Spark for handling bulk data. The best thing I feel is it provides an easy way to configure pipelines so that we were able to process tasks easily using the same. Also apart from this it also helped in monitoring the same. Even for beginners it is very easy to learn. Review collected by and hosted on G2.com.
While doing performance testing it took a lot of time for around 8-10 million records. That could be improved further. Also I think there is a scope to improve the details of errors in a more detailed way. Review collected by and hosted on G2.com.
