JumpMind SymmetricDS vs StreamSets comparison

Why PeerSpot?

The compared JumpMind and IBM solutions aren't in the same category. JumpMind is ranked #12 in DR , and holds a 4.3% mindshare in the category. IBM is ranked #27 in DI , with an average rating of 9.0, and holds a 1.1% mindshare. Additionally, 100% of JumpMind users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

JumpMind SymmetricDS

Read 2 JumpMind SymmetricDS reviews

2,831 Views
878 Comparison Views

100% willing to recommend

StreamSets

Read 21 StreamSets reviews

4,718 Views
3,633 Comparison Views

100% willing to recommend

JumpMind SymmetricDS

StreamSets

Comparison Buyer's Guide

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Executive Summary

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

Find out what your peers are saying about NetApp, Fivetran, Dell Technologies and others in Data Replication.

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

Buyer's Guide

Data Replication

September 2026

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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

JumpMind SymmetricDS

Average Rating

9.0

Reviews Sentiment

8.3

Number of Reviews

Ranking in other categories

Data Replication (12th)

StreamSets

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Integration (27th)

Mindshare comparison

JumpMind SymmetricDS and StreamSets aren’t in the same category and serve different purposes. JumpMind SymmetricDS is designed for Data Replication and holds a mindshare of 4.3%, up 3.3% compared to last year.
StreamSets, on the other hand, focuses on Data Integration, holds 1.1% mindshare, down 1.4% since last year.

Data Replication Mindshare Distribution
Product	Mindshare (%)
JumpMind SymmetricDS	4.3%
NetApp SnapMirror	7.7%
Vision Solutions Double-Take	6.7%
Other	81.3%

Data Replication

Data Integration Mindshare Distribution
Product	Mindshare (%)
StreamSets	1.1%
SSIS	4.0%
Informatica Intelligent Data Management Cloud (IDMC)	3.8%
Other	91.1%

Data Integration

Featured Reviews

it_user1625691

CEO at a non-profit with 1-10 employees

Fully-featured, good performance, and easy to use and install

We are using it to back up the software across the network to a remote server It is fully featured. It has allowed me to do everything I wanted to do. It is also very easy to use and install. It is pretty self-explanatory, and their support was also very good. Everything is fine. The user…

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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

"It is fully featured, has allowed me to do everything I wanted to do, is very easy to use and install, is pretty self-explanatory, and their support was also very good."

"Customer Service: We have a support contract with Jumpmind. The support resources are readily available and provide expert support to any questions."

"It is fully featured. It has allowed me to do everything I wanted to do."

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

"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."

"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 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."

"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."

"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."

"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."

"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."

More StreamSets pros

Cons

"The user interface could improve. We are looking at some cloud-based databases, and I don't think they support that."

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

"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."

"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."

"There are a few things that can be better."

"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."

"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."

"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."

More StreamSets cons

Pricing and Cost Advice

Information not available

"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."

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

"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."

"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."

"StreamSets is an expensive solution."

"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 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 pricing is affordable for any business."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Construction Company

14%

Manufacturing Company

11%

Comms Service Provider

10%

Healthcare Company

Financial Services Firm

10%

Outsourcing Company

Comms Service Provider

Manufacturing 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

Does JumpMind SymmetricDS support a large array of databases?

Yes, it does. This data replication software works with many popular databases, allowing users to benefit from its services. What's more, it also works with many data warehouses, as well as streami...

See all answers

Is JumpMind SymmetricDS easy to use for beginners?

I didn't start with JumpMind SymmetricDS, I actually started using it at a job when I was a little more introduced to data replication. That made me able to see the good features this software has....

See all answers

Does JumpMind SymmetricDS provide frequent file synchronization?

How often do you need for your data to be synchronized? I'm asking this because different companies use data replication for different purposes. Some use it as simply updating backup, others to giv...

See all answers

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 6% of the time

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Compared 6% of the time

Fivetran vs JumpMind SymmetricDS

Compared 5% of the time

EDB Postgres Replication Server vs JumpMind SymmetricDS

Compared 5% of the time

Dell RecoverPoint vs JumpMind SymmetricDS

Compared 5% of the time

More JumpMind SymmetricDS Competitors

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

Oracle Data Integrator (ODI) vs StreamSets

Compared 4% of the time

More StreamSets Competitors

Product Reports

Buyer's Guide

Data Replication

September 2026

Download JumpMind SymmetricDS product report

Buyer's Guide

StreamSets

September 2026

Download StreamSets product report

Also Known As

SymmetricDS

No data available

Overview

JumpMind SymmetricDS is an advanced data replication and synchronization software designed to meet the demands of modern enterprise environments, ensuring reliable data consistency across diverse systems and platforms.

Making its mark as a trusted tool, JumpMind SymmetricDS efficiently handles high-volume data transfers in distributed architectures. Its ability to support cross-platform databases and operate in heterogeneous environments highlights its adaptability, appealing to enterprises seeking robust data integration and synchronization. Users have applauded its real-time synchronization capabilities, which play a crucial role in facilitating seamless operations.

What are the key features of JumpMind SymmetricDS?

Bidirectional Data Synchronization: Enables real-time data flow, ensuring continuous data accuracy.
Cross-Platform Support: Compatible with multiple databases and systems, enhancing integration flexibility.
Conflict Detection and Resolution: Identifies and resolves data discrepancies efficiently.
Flexible Configuration: Allows customization to fit unique enterprise environments.

What benefits or ROI should users look for?

Reduced Downtime: Enhances operational efficiency by minimizing interruptions.
Cost Savings: Lowers maintenance expenses with efficient resource utilization.
Scalability: Adapts to growing data requirements without performance degradation.
Improved Data Integrity: Maintains consistent and reliable data flow across systems.

In industries like retail and finance, JumpMind SymmetricDS plays a critical role in data integration, supporting omnichannel strategies and enabling precise financial transactions by ensuring data remains consistent and up-to-date across different platforms.

JumpMind

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

SmartMD, Cancer Research UK

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

Find out what your peers are saying about NetApp, Fivetran, Dell Technologies and others in Data Replication. Updated: September 2026.

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