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Confluent vs StreamSets comparison

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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
6.3
Number of Reviews
25
Ranking in other categories
Streaming Analytics (9th)
StreamSets
Average Rating
8.4
Reviews Sentiment
7.0
Number of Reviews
21
Ranking in other categories
Data Integration (28th)
 

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 6.2%, down 8.5% compared to last year.
StreamSets, on the other hand, focuses on Data Integration, holds 1.1% mindshare, down 1.4% since last year.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Confluent6.2%
Databricks7.4%
Apache Flink6.9%
Other79.5%
Streaming Analytics
Data Integration Mindshare Distribution
ProductMindshare (%)
StreamSets1.1%
SSIS4.0%
Informatica Intelligent Data Management Cloud (IDMC)3.8%
Other91.1%
Data Integration
 

Featured Reviews

PavanManepalli - PeerSpot reviewer
AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo
Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing
I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.
SS
Enterprise Solutions Architect at a energy/utilities company with 1,001-5,000 employees
Enables effective batch loading with visual interface and enterprise support
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. I had to switch to a new EC2 box, even though the processor was not fully utilized. It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades. Additionally, it would be a great enhancement if StreamSets could produce a lineage graph to visualize how the data has passed through the system.

Quotes from Members

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

Pros

"As an enterprise organization, data availability is critical and Confluent provides that SLA support."
"The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka."
"Overall, it's a great company and they have excellent software."
"Our main goal is to validate whether we can build a scalable and cost-efficient way to replicate data from these various sources."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"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."
"The client APIs are the most valuable feature."
"The biggest benefit of Confluent as a tool is that it is a distributed platform that provides more durability and stability."
"It has helped us in moving into the data analytics world at a faster pace than any other tool would have done."
"This product was a lot easier to use than the one we had before it, and it took us half an hour and we were set up and running it the first time."
"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 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 most valuable features are the option of integration with a variety of protocols, languages, and origins."
"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."
"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."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source systems."
 

Cons

"The beginner who doesn't know how to work on HTML will struggle as when you create spaces in the Confluent, if you want to have some meeting notes or anything else, you need to know HTML and which HTML tags to include."
"I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team."
"Confluent has a good monitoring tool, but it's not customizable."
"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."
"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."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"It could have more themes. They should also have more reporting-oriented plugins as well. It would be great to have free custom reports that can be dispatched directly from Jira."
"From the control center perspective, there is a lot of room for improvement in the visualization."
"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."
"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."
"There are a few things that can be better."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"StreamSet works great for batch processing but we are looking for something that is more real-time. We need latency in numbers below milliseconds."
"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"If the data processing in StreamSets takes a long time as compared to the previous solution, then we will reconsider why we use StreamSets."
 

Pricing and Cost Advice

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"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."
"The solution is cheaper than other products."
"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 an expensive solution."
"It comes with a high cost."
"Confluent is highly priced."
"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 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."
"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."
"The pricing is affordable for any business."
"It's not so favorable for small companies."
"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."
"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
14%
Retailer
12%
Manufacturing Company
7%
Construction Company
6%
Financial Services Firm
10%
Outsourcing Company
9%
Comms Service Provider
8%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise4
Large Enterprise17
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise11
 

Questions from the Community

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 recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about ...
What is your primary use case for Confluent?
The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...
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.
What advice do you have for others considering StreamSets?
If asked, I definitely recommend StreamSets to other users. My overall rating for the solution is nine.
 

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 Databricks, Microsoft, Apache and others in Streaming Analytics. Updated: September 2026.
917,433 professionals have used our research since 2012.