Hevo vs StreamSets comparison

Why PeerSpot?

Hevo Data and IBM are both solutions in the Data Integration category. Hevo Data is ranked #49 with an average rating of 7.0, while IBM is ranked #24 with an average rating of 9.5. Hevo Data holds a 0.5% mindshare in DI, compared to IBM’s 1.1% mindshare. Additionally, 100% of Hevo Data users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Hevo

Read 1 Hevo review

1,137 Views
1,126 Comparison Views

100% willing to recommend

StreamSets

Read 21 StreamSets reviews

4,501 Views
3,466 Comparison Views

100% willing to recommend

Hevo

StreamSets

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Hevo and StreamSets based on real PeerSpot user reviews.

Find out what your peers are saying about Informatica, Palantir, Microsoft and others in Data Integration.

To learn more, read our detailed Data Integration Report (Updated: September 2026).

Buyer's Guide

Data Integration

September 2026

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Helped 913,806 peers since 2012

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

Hevo

Ranking in Data Integration

49th

Average Rating

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

StreamSets

Ranking in Data Integration

24th

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Data Integration category, the mindshare of Hevo is 0.5%, up from 0.3% compared to the previous year. The mindshare of StreamSets is 1.1%, down from 1.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
StreamSets	1.1%
Hevo	0.5%
Other	98.4%

Data Integration

Featured Reviews

davidmwilliams

CIO / CTO / Head Of Data at Data Excellence

Centralizes customer data for fast analytics but has struggled with many concurrent data pipelines

Hevo could be improved as we hit limits, particularly when it couldn't keep up with the high number of databases we wanted to sync frequently—ideally updating everything hourly for near real-time analytics rather than a day behind. We found that with many pipelines, performance degraded. After discussing with Hevo engineers, I learned that Hevo is designed for fast individual pipelines, but struggles with many concurrent pipelines. They suggested that consolidating data from fewer pipelines with more fields would perform better, but even that failed when I tested it with a Business Central database that had numerous fields. Hevo does have limits on the number of pipelines it can manage concurrently and on the number of fields in a single pipeline.Additionally, the API was slower to release compared to the user interface and was not feature-complete, which was frustrating. That said, Hevo actively worked on bridging many gaps. Overall, these were significant pain points I encountered.

Read full review

SrinivasanSankar

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.

Read full review

Quotes from Members

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

Pros

"Hevo positively impacted my organization by allowing us to move data quickly and easily, enabling us to focus on our real challenge: performing analytics and reporting out of Snowflake with all customer data centralized despite using various applications."

"StreamSets' reusable assets have helped to reduce workload by 32% to 40%."

"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."

"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."

"In StreamSets, everything is in one place."

"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 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."

"StreamSets has definitely helped us in getting the information into our data lake very quickly, in terms of ingestion, and the most important thing is it has helped us from a resourcing point of view because you can easily upskill a BI or ETL resource without any programming knowledge to work with this, which has drastically reduced the time that we are spending on workloads by 60% to 70% as well as reducing the time spent on ingestion by 30%."

"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."

More StreamSets pros

Cons

"Hevo could be improved as we hit limits, particularly when it couldn't keep up with the high number of databases we wanted to sync frequently—ideally updating everything hourly for near real-time analytics rather than a day behind."

"We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back."

"If you use JDBC Lookup, for example, it generally takes a long time to process data."

"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."

"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."

"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."

"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."

"Visualization and monitoring need to be improved and refined."

"The monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."

More StreamSets cons

Pricing and Cost Advice

Information not available

"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."

"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 pricing is affordable for any business."

"I believe the pricing is not equitable."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

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

"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."

"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."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

10%

Outsourcing Company

Comms Service Provider

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	9
Midsize Enterprise	2
Large Enterprise	11

Questions from the Community

What needs improvement with Hevo?

See all answers

What is your primary use case for Hevo?

My main use case for Hevo is moving data from a series of different databases into a Snowflake data warehouse.I can give you a specific example of how I use Hevo to move data between databases and ...

See all answers

What advice do you have for others considering Hevo?

Hevo did not have any AI capabilities when I was using it, but I think its security is good, utilizing proper web authentication techniques with encrypted keys. However, it does not enforce governa...

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What needs improvement with StreamSets?

See all answers

What is your primary use case for StreamSets?

We are using StreamSets for batch loading.

See all answers

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.

See all answers

Comparisons

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Compared 24% of the time

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Compared 22% of the time

Fivetran vs Hevo

Compared 20% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs Hevo

Compared 11% of the time

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Pentaho Data Integration and Analytics vs StreamSets

Compared 9% of the time

Informatica PowerCenter vs StreamSets

Compared 6% of the time

SSIS vs StreamSets

Compared 6% of the time

Spring Cloud Data Flow vs StreamSets

Compared 5% of the time

Confluent vs StreamSets

Compared 4% of the time

More StreamSets Competitors

Product Reports

Buyer's Guide

Data Integration

September 2026

Download Hevo product report

Buyer's Guide

StreamSets

August 2026

Download StreamSets product report

Overview

Hevo is an intuitive data integration platform designed to streamline real-time data collection and analysis for businesses. It offers a seamless way to automate data pipelines, eliminating the complexities associated with data management and integration.

Hevo provides an efficient data integration service that enables organizations to connect data from a range of sources into a unified destination for better analysis and decision-making. By supporting real-time data processing, Hevo helps businesses maintain updated analytics, ensuring they can quickly react to changing trends. With its no-code platform, it helps reduce dependency on IT teams, accelerating the integration process and facilitating quicker insights. This platform is suitable for businesses looking to simplify their data workflows and empower their analytics teams.

What are the key features of Hevo?

No-Code Data Pipelines: Build without technical expertise, enabling faster deployment of workflows.
Real-Time Data Processing: Ensure timely analytics to support immediate data-driven decisions.
Seamless Integrations: Connect with a broad range of data sources effortlessly.
Automated Schema Management: Adjust to changes in data walkthrough automation, reducing manual interventions.

What benefits should users expect from using Hevo?

Improved Efficiency: Automation reduces manual tasks, freeing up resources for strategic initiatives.
Enhanced Agility: Adapt swiftly to data changes, improving response times to market dynamics.
Cost Savings: Minimized need for technical resources lowers operational expenses.
Scalable Solutions: Flexible infrastructure supports growth without compromising performance.

Hevo is widely adopted across industries such as e-commerce, finance, and healthcare, where it facilitates efficient data integration and analytics. In e-commerce, Hevo aids in real-time inventory and customer insights. Financial sectors leverage it for fraud detection and compliance analysis, while healthcare providers use it to integrate patient data for improved outcomes.

Hevo Data

StreamSets streamlines data pipeline creation, connecting data from multiple sources to destinations like cloud platforms with minimal coding. Its centralized platform and intuitive design enhance ETL and data migration processes.

StreamSets integrates seamlessly with analytics platforms, offering tools such as Data Collector and Control Hub to facilitate data ingestion, transformation, and machine learning integrations. Its user-friendly interface and ready connectors aid in configuring complex data pipelines. With built-in data drift resilience and scheduling options, users experience efficient, scalable data management, despite challenges like latency in cloud storage and interface enhancement needs. Users often employ StreamSets for batch loading, real-time data processing, and smart data pipeline management, offering comprehensive data integration solutions.

What are the key features of StreamSets?

Data Collector: Enables streamlined data collection and processing.
Control Hub: Centralizes management of data pipelines.
Minimal Coding: Simplifies pipeline configuration with limited code requirement.
Data Drift Resilience: Adapts to changes in data patterns effectively.

What benefits should users look for?

Time-Saving: Efficient processes reduce manual effort.
Scalability: Easily manages large datasets.
Integration: Connects with leading analytics and cloud platforms.
Real-Time Processing: Supports continuous data delivery for timely insights.

In industries like finance and technology, StreamSets supports data migration, machine learning integrations, and analytics by simplifying data transformation and enhancing decision-making capabilities through its robust pipeline management.

IBM

Sample Customers

Deliverr, Meesho, Byju's, Envato, NZXT, Kazoo, Webedia, Airwallex, Cuvva, Opploans

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

Find out what your peers are saying about Informatica, Palantir, Microsoft and others in Data Integration. Updated: September 2026.

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