CloverETL vs StreamSets comparison

Javlin and IBM are both solutions in the Data Integration category. Javlin is ranked #60, while IBM is ranked #23 with an average rating of 8.8. Javlin holds a 0.2% mindshare in DI, compared to IBM’s 1.6% mindshare. Additionally, 100% of Javlin users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

CloverETL

Read 2 CloverETL reviews

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167 Comparison Views

100% willing to recommend

StreamSets

Read 21 StreamSets reviews

2,082 Views
1,312 Comparison Views

100% willing to recommend

CloverETL

StreamSets

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Executive SummaryUpdated on Dec 19, 2024

CloverETL and StreamSets compete in the data integration market, each designed for complex data tasks. StreamSets has the upper hand due to its advanced real-time processing and integration features, although CloverETL is more budget-friendly.

Features: CloverETL offers strong data transformation capabilities, robust scheduling tools, and adaptable integration. StreamSets focuses on real-time data processing, scalable architecture, and advanced integration suited for cloud-native applications.

Ease of Deployment and Customer Service: StreamSets provides a flexible deployment model supporting both on-premises and cloud environments, easing integration with existing systems, along with comprehensive customer support. CloverETL uses a traditional deployment method requiring setup but provides attentive service to customers.

Pricing and ROI: CloverETL is seen as more cost-effective with lower initial setup costs, appealing to budget-conscious organizations seeking predictable ROI. StreamSets, while having higher investment costs, justifies the price with features that appeal to businesses looking for scalability and improved operational efficiency.

To learn more, read our detailed CloverETL vs. StreamSets Report (Updated: May 2025).

Buyer's Guide

CloverETL vs. StreamSets

May 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

CloverETL

Ranking in Data Integration

60th

Average Rating

7.0

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

Data Visualization (40th)

StreamSets

Ranking in Data Integration

23rd

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Data Integration category, the mindshare of CloverETL is 0.2%, up from 0.1% compared to the previous year. The mindshare of StreamSets is 1.6%, up from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

it_user856614

Lead Programmer at a healthcare company with 10,001+ employees

Very easy to schedule jobs and monitor them, however we run out heap space even with a high allocation

Flexibility: We can bring in data from multiple sources, e.g., databases, text files, JSON, email, XML, etc. This has been very helpful Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility. Server features for scheduler: It is…

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Ved Prakash Yadav

Senior Data Platform Manager at a manufacturing company with 10,001+ employees

Useful for data transformation and helps with column encryption

We use various tools and alerting systems to notify us of pipeline errors or failures. StreamSets supports data governance and compliance by allowing us to encrypt incoming data based on specified rules. We can easily encrypt columns by providing the column name and hash key. If you're considering using StreamSets for the first time, I would advise first understanding why you want to use it and how it will benefit you. If you're dealing with change tracking or handling large amounts of data, it could be cost-effective compared to services like Amazon. It's easy to schedule and manage tasks with the tool, and you can enhance your skills as an ETL developer. You can easily migrate traditional pipelines built on platforms like Informatica or Talend to StreamSets. I rate the overall solution an eight out of ten.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."

"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."

"Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."

"No dependence on native language and ease of use."

"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."

"The ability to have a good bifurcation rate and fewer mistakes is valuable."

"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."

"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."

"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."

"The entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."

"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."

More StreamSets pros

Cons

"Its documentation could be improved."

"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."

"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."

"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."

"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."

"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."

"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."

"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."

"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."

"We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which was painful. Also, pipeline failures were common, and data drifting wasn't addressed, which made things worse. Licensing was another issue we encountered."

"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."

More StreamSets cons

Pricing and Cost Advice

Information not available

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"It's not so favorable for small companies."

"It has a CPU core-based licensing, which works for us and is quite good."

"StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."

"We are running the community version right now, which can be used free of charge."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

"The pricing is affordable for any business."

"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

12%

Computer Software Company

11%

Manufacturing Company

10%

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

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What needs improvement with StreamSets?

One issue I observed with StreamSets is that the memory runs out quickly when processing large volumes of data. Because of this memory issue, we have to upgrade our EC2 boxes in the Amazon AWS infr...

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What is your primary use case for StreamSets?

We are using StreamSets for batch loading.

See all answers

Comparisons

No data available

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Compared 13% of the time

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Compared 13% of the time

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Compared 9% of the time

Azure Data Factory vs StreamSets

Compared 7% of the time

Fivetran vs StreamSets

Compared 6% of the time

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Product Reports

Buyer's Guide

Data Integration

June 2025

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Buyer's Guide

StreamSets

June 2025

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Overview

CloverETL is a rapid, end-to-end data integration solution. Businesses choose CloverETL for its usability and intuitive controls, along with its lightweight footprint, flexibility, and processing speed. Achieving true, rapid data integration means much more than just raw data processing power. Rapid refers to an end-to-end process that begins the moment a data-related problem is recognized to the point when the data is in the right place and form to be analyzed and monetized.

Javlin

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

IBM

Sample Customers

IBM, Oracle, MuleSoft, GoodData, Thomson Reuters, salesforce.com, Comcast, Active Network, SHOP.CA

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

CloverETL vs. StreamSets

May 2025

Free Report: CloverETL vs. StreamSets

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