IBM StreamSets Reviews & Product Details

The thing that I most like about stream sets is that it makes building real time data integration and pipeline building is made very smooth. The drag and drop interface is easy to use. Also it connects to various data sources and destinations. It has cool built in monitoring and error handling mechanisms to help keep out an eye on the health of your pipeline. I also enjoy how scalable it is. I mean you can use it on a small project to something enterprise level project. Review collected by and hosted on G2.com.

it can be tricky to get started directly with streamsets especially if you are at beginner level. Like if you don't have any experience prior about data engineering. You need deeper level of understanding to use some advanced features but I think the documentation is helpful sometimes but not always. Also the pricing seems steep for small teams. Review collected by and hosted on G2.com.

StreamSets continues to offer an intuitive drag-and-drop canvas that simplifies pipeline creation. The seamless integration with key-vaults for secure secret management and the ease of scheduling pipelines remain strong features. It's beginner-friendly and gets data flowing quickly, especially for teams with limited coding background. Review collected by and hosted on G2.com.

While StreamSets was once a frontrunner in visual pipeline design, modern cloud-native tools have leapfrogged it. Platforms like Azure Data Factory, Amazon EMR notebooks, and Apache Airflow now offer more flexibility, deeper integrations, and better support for orchestration, monitoring, and cost control. Adding richer developer features, tighter CI/CD capabilities, and improved scalability options would help StreamSets stay relevant in today’s fast-evolving data engineering landscape. Review collected by and hosted on G2.com.

It excels at simplifying complex data integration workflows.

It's visual pipeline design makes it's intutive so that anyone can build ,deploy and test in most of the cases.

It supports wide range of connectors for real time data and batch processing .

Most effective feature of it is that it has built in data observation ability and lineage tracking.

This feature gives confidence to the team for their data pipeline reliability and compliance reporting .

This also handels high loads and made for high scalabilty & high throughput. Review collected by and hosted on G2.com.

It has steep learning curve, especially when u have use some advance features deep technical knowledge of data engineering and related fields is required.

UI feels sometimes little sluggish and cluttered when operator has to deal with complex pipelines.

It's bit costlier for smaller teams or startups, if they want to purchase the enterprise-level licensing model . Review collected by and hosted on G2.com.

I like how StreamSets makes building and managing data pipelines very intuitive with its drag-and-drop interface. It supports real-time streaming as well as batch processing, and the built-in monitoring/alerts give great visibility into pipeline health and data quality. Review collected by and hosted on G2.com.

Some advanced features have a steep learning curve, and the platform can feel resource-intensive at times. Documentation could be more detailed, and faster response from support would make the experience even better. Review collected by and hosted on G2.com.

The platform’s growing support for automation, reusability, and real-time processing makes it not just an ETL tool, but a full-fledged DataOps platform. Review collected by and hosted on G2.com.

IBM Stream Sets is a powerful platform, but it can improve in a few key areas. Handling highly complex or customized integrations can be challenging, and connector support for some newer cloud services could be expanded. The learning curve for Control Hub and CI/CD automation is a bit steep for new users, and error messages during pipeline failures could be more detailed to help with faster troubleshooting. Review collected by and hosted on G2.com.

user-friendly, visual, low-code/no-code interface that simplifies data pipeline creation with a drag-and-drop approach Review collected by and hosted on G2.com.

i couldnt think any reason to dislike it Review collected by and hosted on G2.com.

1. Works well in real-time and batches

2. Low code visual UI

3. Easier deployment

4. Probably work well with IBM ecosystem. But not tried yet. Review collected by and hosted on G2.com.

1. Enterprise grade costing would be tricky.

2. Though simple features are easier to learn but advanced ones are complex and time taking whole learning.

3. Overall limited community of IBM ecosystem I'm compare to competitors Review collected by and hosted on G2.com.

I really like how IBM StreamSets now works with watsonx—it makes building and managing data pipelines feel a lot smoother. The smart automation, clear data tracking, and built-in quality checks save time and reduce guesswork.

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One thing IBM StreamSets could improve is making the interface a bit more beginner-friendly. Also, faster and clearer error messages during pipeline issues would really help save time and reduce frustration.

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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.