StreamSets vs Striim comparison

Why PeerSpot?

IBM and Striim are both solutions in the Data Integration category. IBM is ranked #24 with an average rating of 9.5, while Striim is ranked #46 with an average rating of 7.7. IBM holds a 1.1% mindshare in DI, compared to Striim’s 0.6% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 100% of Striim users who would recommend it.

StreamSets

Read 21 StreamSets reviews

4,501 Views
3,466 Comparison Views

100% willing to recommend

Striim

Read 4 Striim reviews

2,209 Views
1,347 Comparison Views

100% willing to recommend

StreamSets

Striim

Comparison Buyer's Guide

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Executive Summary

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

Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed StreamSets vs. Striim Report (Updated: September 2026).

Buyer's Guide

StreamSets vs. Striim

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

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

Striim

Ranking in Data Integration

46th

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

Cloud Data Integration (25th), Streaming Analytics (22nd)

Mindshare comparison

As of September 2026, in the Data Integration category, the mindshare of StreamSets is 1.1%, down from 1.4% compared to the previous year. The mindshare of Striim is 0.6%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration Mindshare Distribution
Product	Mindshare (%)
StreamSets	1.1%
Striim	0.6%
Other	98.3%

Data Integration

Featured Reviews

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

Ramakanth Vanga

Data Engineer

Real-time data capture has accelerated releases and now improves trust in our data warehouse

The checkpoints would help me to figure out where the problem was if there's any lag, but I had to do a lot of manual work to figure out where the lag is. Striim would not intuitively tell me the culprit table or database behind the lag. I believe that is an improvement Striim could definitely do. Passwords were an issue. Property variables were not supported for passwords, meaning I had to make sure the password is manually populated. I believe if Striim could read from AWS secrets or its own secret mechanism to store the password, that would really save a lot of time so that I don't have to keep updating the password whenever there is any change. The user experience of triggering alerts if there's any lag which Striim identified, which is outside normal processing time, could intrinsically be done by Striim. I believe that was lacking. I would wait for Striim to tell me, instead of me going and validating whether Striim is lagging behind. If Striim could itself tell me that it's seeing a lot more volume than expected, that would really make me give it a higher number.

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

"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."

"StreamSets is the leader in the market."

"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."

"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 feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."

"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."

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

"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."

More StreamSets pros

"We were confidently in a situation to call Snowflake as a single source of truth, and I believe with Striim, we were able to do that because without Striim, the SLA would be much higher, and there would not have been much confidence in Snowflake."

"Striim acts as the perfect modern bridge for legacy environments, keeping both our development teams and business stakeholders happy."

"Striim is definitely my data migration tool and data reflection syncing tool. It reduces manual intervention because it automatically syncs the data from the warehouse."

"Striim is capable of absorbing a large number of transactions, and the difference between the two databases is always less than a second, which demonstrates efficiency and highlights the variety of sources and targets I have used."

Cons

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

"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."

"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."

"If the data processing in StreamSets takes a long time as compared to the previous solution, then we will reconsider why we use StreamSets."

"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."

"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."

"The documentation is inadequate and has room for improvement because the technical support does not regularly update their documentation or the knowledge base."

"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

"I would say Striim performance needs improvement because we use more GoldenGate, so I tend to compare GoldenGate with Striim."

"I think Striim could be improved with better pricing and enhanced documentation."

"The user experience of triggering alerts if there's any lag which Striim identified, which is not normal, could intrinsically be done by Striim."

"I think the initial schema mapping tool in Striim can have a learning curve when dealing with deeply nested mainframe structures or complex copybooks."

Pricing and Cost Advice

"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."

"I believe the pricing is not equitable."

"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 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."

"StreamSets is an expensive solution."

"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."

"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."

More StreamSets pricing and cost advice

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

10%

Outsourcing Company

Comms Service Provider

Healthcare Company

Retailer

17%

Construction Company

13%

Healthcare Company

12%

Financial Services Firm

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

No data available

Questions from the Community

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

What is your experience regarding pricing and costs for Striim?

It's very fair. We had a private cloud, and it's not based on the number of events. It was based on the number of cores and CPU cores.

See all answers

What needs improvement with Striim?

See all answers

What is your primary use case for Striim?

We were using batch data from an Oracle database, which was causing the Oracle database to slow down. We enabled change data capture and used Striim to read data from Oracle databases and ingest in...

See all answers

Comparisons

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

Qlik Talend Cloud vs Striim

Compared 13% of the time

Upsolver vs Striim

Compared 9% of the time

Oracle GoldenGate vs Striim

Compared 9% of the time

AWS Database Migration Service vs Striim

Compared 8% of the time

Confluent vs Striim

Compared 8% of the time

More Striim Competitors

Product Reports

Buyer's Guide

StreamSets

August 2026

Download StreamSets product report

Buyer's Guide

Streaming Analytics

September 2026

Download Striim product report

Also Known As

No data available

Striim Platform

Overview

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

Striim offers a comprehensive platform for real-time data integration and streaming analytics, designed to streamline data processes for enterprise-level solutions.

Striim enables seamless migration and integration of data across cloud and on-premises environments, making it ideal for businesses looking to leverage real-time analytics. Its capabilities support continuous data flow, reducing latency and enhancing decision-making. Designed for scalable and secure data management, Striim facilitates effective data-driven strategies.

What are some key features of Striim?

Continuous Data Ingestion: Collects and processes real-time data streams promptly.
Data Integration: Combines data from different sources for unified insights.
Real-Time Analytics: Supports instant analytics, allowing fast response to changes.
Scalable Architecture: Adapts to large-scale data environments efficiently.

What benefits should users look for in Striim reviews?

Improved Data Accuracy: Ensures data integrity in analytics.
Enhanced Operational Efficiency: Streamlined processes for faster data handling.
Cost-Effective Integration: Reduces expenses associated with traditional data handling.
Flexible Deployment Options: Allows for tailored solutions fitting specific needs.

In industries like finance, Striim supports real-time fraud detection by providing uninterrupted data streaming between transaction systems. In healthcare, it enables rapid data processing for patient monitoring, improving service delivery. Manufacturing uses Striim to enhance supply chain visibility through real-time data analytics.

Striim

Sample Customers

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

Sky, UPS, MACY'S, EMAAR, HSBC

Buyer's Guide

StreamSets vs. Striim

September 2026

Free Report: StreamSets vs. Striim

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