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Confluent vs StreamSets comparison

 

Comparison Buyer's Guide

Executive Summary

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

Confluent
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
23
Ranking in other categories
Streaming Analytics (4th)
StreamSets
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
21
Ranking in other categories
Data Integration (16th)
 

Mindshare comparison

Confluent and StreamSets aren’t in the same category and serve different purposes. Confluent is designed for Streaming Analytics and holds a mindshare of 8.2%, down 11.2% compared to last year.
StreamSets, on the other hand, focuses on Data Integration, holds 1.6% mindshare, up 1.4% since last year.
Streaming Analytics
Data Integration
 

Featured Reviews

Gustavo-Barbosa Dos Santos - PeerSpot reviewer
Has good technical support services and a valuable feature for real-time data streaming
Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance. It helps us understand the various requirements of multiple customers and validates the information for different versions. We can automate the tasks using Confluent Kafka. Thus, it guarantees us the data quality and maintains the integrity of message contracts.
Nantabo Jackie - PeerSpot reviewer
Simplified pipelines and helped us break down data silos within our organization
The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

Quotes from Members

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

Pros

"Their tech support is amazing; they are very good, both on and off-site."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"The documentation process is fast with the tool."
"The benefit is escaping email communication. Sometimes people ignore emails or put them into spam, but with Confluence, everyone sees the same text at the same time."
"It is also good for knowledge base management."
"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."
"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."
"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"
"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."
"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."
"The best feature that I really like is the integration."
"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."
"One of the things I like is the data pipelines. They have a very good design. Implementing pipelines is very straightforward. It doesn't require any technical skill."
 

Cons

"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."
"It could have more integration with different platforms."
"The pricing model should include the ability to pick features and be charged for them only."
"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."
"I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"In Confluent, there could be a few more VPN options."
"It requires some application specific connectors which are lacking. This needs to be added."
"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 documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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 infrastructure."
"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"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."
 

Pricing and Cost Advice

"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."
"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"It comes with a high cost."
"Confluent is an expensive solution."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"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."
"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."
"I believe the pricing is not equitable."
"StreamSets is an expensive solution."
"It has a CPU core-based licensing, which works for us and is quite good."
"We are running the community version right now, which can be used free of charge."
"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."
"The pricing is affordable for any business."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
16%
Manufacturing Company
7%
Insurance Company
6%
Financial Services Firm
13%
Computer Software Company
11%
Manufacturing Company
10%
Insurance Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Confluent?
I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...
What is your experience regarding pricing and costs for Confluent?
They charge a lot for scaling, which makes it expensive.
What needs improvement with Confluent?
I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team. The lack of easy access to the Confluent support team is also a...
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...
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...
What is your primary use case for StreamSets?
We are using StreamSets for batch loading.
 

Comparisons

 

Overview

 

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge
Find out what your peers are saying about Confluent vs. StreamSets and other solutions. Updated: April 2025.
851,604 professionals have used our research since 2012.