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.

StreamSets makes designing and managing data pipelines easy-peasy. Its versatility and vast array of connectors simplify the process of handling different data sources. It's like having a smooth operator for your data flow. Review collected by and hosted on G2.com.

While StreamSets offers many benefits, some users find its learning curve a bit steep initially. Additionally, the complexity of certain configurations might be overwhelming for beginners. Review collected by and hosted on G2.com.

The tool has userfriendly interface, which has simplified the process of designing data pipelines. The number of connectors has made it easy for me to integrate various data sources. Also an additional thing is that it can handle both stream and batch data. In the organisation, the client has migrated to StreamSets and it is used almost 80% of the time. The team is quite accessible in case of any defects raised and is very co-orperative. Review collected by and hosted on G2.com.

Down sides of using SteamSets might be the cost, for some scenarios the solution might be costlier than the competition, For Large scale data there have been reports of performance issues. Review collected by and hosted on G2.com.

Streamsets is a good and lightweight integration tool with good ease of integration. It's fast and reliable. It has a decent library of connectors which are easy to use. I have been using streamsets for a year now and recently switched to data bricks. Customer support turnaround is decent. Ease of implementation is not that good as the learning curve is high without a good resource to study from Review collected by and hosted on G2.com.

lack of documentation and community support Review collected by and hosted on G2.com.

It's very easy to build pipelines. Just drag and drop components and the coding can we done within the components. We can use a wide range of tech and languages to get our data transformation done. We can also connect to different DBs. Also modifying the pipelines and deploying it is very easy. Review collected by and hosted on G2.com.

Probably if we make a change to any jar components in the spark evaluator or add any component to the files in StreamSets , we need to restart the server. Review collected by and hosted on G2.com.

I've had a very positive overall experience with streamsets. Streamsets are a tool that our organization uses to migrate its on-premises data to the cloud, it is a potent tool that can assist us in our cloud migration journey by connecting to numerous tools, such as Hadoop and Teradata, with ease. Review collected by and hosted on G2.com.

So far i have observed that debugging becomes difficult when utilizing a large dataset because the pipeline fails without generating a specific error. It cannot establish parallel connections with Teradata to speed up pipeline execution. Review collected by and hosted on G2.com.

Streamsets is having functions to built,check,observe and change the data pipeline which are momently providing data. Review collected by and hosted on G2.com.

StreamSets can handle a lot of data sources and destinations, but it struggles a bit with some fancy proprietary systems. Review collected by and hosted on G2.com.

I love using streamsets because it helps in moving data and make necessary transformations to the data by using processors. Review collected by and hosted on G2.com.

As of now I haven't faced any issues for this. Review collected by and hosted on G2.com.

StremSets User interface is very useful friendly. It provides drag and drop facility which simplifies building, designing and managing the data pipelines.

It also handles a very large amount of data since it is scalable.

We can use it for building both batch pipelines and streaming pipelines.

It also provides security features such as encryption, access controls, data masking etc.

The team also provides a very good customer support.

Since it has drag and drop functionality we can easily implement and integrate it with different sources and destination. Review collected by and hosted on G2.com.

As of now I don't have any dislikes about StreamSets since it is improving a lot. Review collected by and hosted on G2.com.

The fact that it allows you to orchestrate your data pipelines with minimal coding and with not-so-deep understading of DE/ETL concepts is super helpful. Also, Streamsets data collector is an open source tool to be used for data ingestion and integration usecases. Review collected by and hosted on G2.com.

Few things I could say where they came short.

1. Their pricing structure is rather ambigous and could be hard to decode while choosing the right version for your usecase

2.For some data sources, streamsets may not be have connectors as compared to other tools in the market.

3. With the GUI based tool, and being on pricey end, there is always long term maintenance ovehead which makes more problems that it solves.

4. They offer customer support via third party zendesk and their documentation resources aren't comprehensive enough in my experience Review collected by and hosted on G2.com.