Fivetran vs. IBM StreamSets

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

Incentivized

IBM StreamSets excels in real-time logistics data ingestion and transformation across hybrid systems. It’s less ideal for lightweight ETL tasks or static datasets where simpler tools can achieve similar results with less overhead and complexity.

Incentivized

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

Incentivized

• It helps streaming huge data that we have in our Teradata database to various reporting applications that runs on cloud seamlessly.
• We also use IBM StreamSets to power few BI dashboards that our product managers use on regular basis to showcase various data with clients.
• I think the data quality is way better compared to Informatica tool.

Incentivized

• Very difficult to get connectors enhanced if a specific needed object is not supported by them
• Depending on the edition needed and the data volumes, can get quite expensive

Incentivized

• The error messages I feel aren t always very descriptive so troubleshooting can take longer
• Maybe more customisation options for scheduling can be done, rest it works pretty well.

Incentivized

IBM Stream sets has been a wonderful addition to our technology stack. It has helped in some of our initiatives such as data engineering, data integration for not only external customers but also for internal purposes. The tool has also helped on our use cases related to streaming data. Moving to another tool would require significant amount of work and time.

Incentivized

Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

Incentivized

The StreamSets platform is very easy to use and the interface is extremely intuitive. The drag-and-drop, low-code design makes it accessible for teams with varying technical skills, allowing us to quickly connect sources, define transformations, and deploy pipelines without heavy coding. StreamSets allows us to get started quickly and not have to worry about our pipelines breaking once they're built.

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

Streamsets support has improved a lot in the last couple of years. We had some challenges in the beginning with support, but now the quality of the support and the responsiveness to tickets are better. We have contacted support multiple times when it came to scenarios where the system was slow or the output as not as we expected

Incentivized

I was not involved in the implementation

Incentivized

We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

Incentivized

First advantage is that this software is particularly new and it keeps updating according to the needs of the user. Other advantage is the it organises and produces conclusions on the basis of data without leaving any relevant information. Other softwares lack in data summarising and readability of the charts and sheets they produce.

Incentivized

• It has been very positive in serving BI team with new source requests
• It has been OK at scaling to match as data volumes as source data size grows

Incentivized

• time saving for automatic collection and integration of data
• time saving thanks to live monitoring and reaction
• time saving for standardization of data

Incentivized