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Talend Data Fabric vs Upsolver 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

Talend Data Fabric
Ranking in Data Integration
33rd
Average Rating
8.4
Reviews Sentiment
6.5
Number of Reviews
8
Ranking in other categories
No ranking in other categories
Upsolver
Ranking in Data Integration
39th
Average Rating
8.6
Reviews Sentiment
7.6
Number of Reviews
4
Ranking in other categories
Streaming Analytics (21st)
 

Mindshare comparison

As of August 2026, in the Data Integration category, the mindshare of Talend Data Fabric is 0.8%, down from 1.0% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Talend Data Fabric0.8%
Upsolver0.7%
Other98.5%
Data Integration
 

Featured Reviews

Salini Ravindranath - PeerSpot reviewer
Solution Architect at Spire Solutions
Data governance has improved and complex integrations are handled with flexible customization
Regarding Talend Data Fabric, the ease of use and the customization options that are available are particularly valuable. There are a lot of built-in components and features that we can modify in any way we want to transform the data and make it analytics ready. Talend Data Catalog is another product that, when combined with Talend Data Fabric, can be used for the data governance. The stewardship, ownership, and curation happen mainly from the Data Catalog side. Within Talend Data Fabric, the role-based access control is used for user segregations such as security, infrastructure-related or integration-related activities. It bifurcates the roles and responsibilities. From the data standpoint, the RBAC functions with the help of Data Catalog.
reviewer2784462 - PeerSpot reviewer
Software Engineer at a tech vendor with 10,001+ employees
Streaming pipelines have become simpler and onboarding new data sources is now much faster
One of the best features Upsolver offers is the automatic schema evolution. Another good feature is SQL-based streaming transformations. Complex streaming transformations such as cleansing, deduplication, and enrichment were implemented using SQL and drastically reduced the need for custom Spark code. My experience with the SQL-based streaming transformations in Upsolver is that it had a significant positive impact on the overall data engineering workflow. By replacing custom Spark streaming jobs with declarative SQL logic, I simplified development, review, and deployment processes. Data transformations such as parsing, filtering, enrichment, and deduplication could be implemented and modified quickly without rebuilding or redeploying complex code-based pipelines. Upsolver has impacted my organization positively because it brings many benefits. The first one is faster onboarding of new data sources. Another one is more reliable streaming pipelines. Another one is near-real-time data availability, which is very important for us. It also reduced operational effort for data engineering teams. A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days. Custom Spark code reduction reached 50 to 40 percent. Pipeline failures are reduced by 70 to 80 percent. Data latency is improved from hours to minutes.

Quotes from Members

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

Pros

"It is a smart tool for us to design data pipelines. It lets us populate our three data lake instances. We like this solution for its connection capabilities, since it is very important to be able to use many different types of software. We tested a lot of SAP sources successfully, including cloud sources with SAP. It is also very easy to anonymize data with TIBCO, as well as populating HDFS files, packet files, and raw files. It is very easy to do that with Talend Data Fabric."
"Everything in Talend Data Fabric is GUI-based, making it very user-friendly and easy to learn quickly."
"The Talend data integration has been one of the most valuable features."
"Talend has very good support for big data."
"We've had no issues with the stability so far."
"What I find most valuable about this solution is the 900 connectors because it allows me to integrate any tool and any cloud system I need to integrate and they have a connector out of the box."
"There are a lot of built-in components and features that we can modify in any way we want to transform the data and make it analytics ready."
"The initial setup is very easy."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days, custom Spark code reduction reached 50 to 40 percent, pipeline failures are reduced by 70 to 80 percent, and data latency is improved from hours to minutes."
"I have saved 50 to 60% on maintaining pipelines since using Upsolver."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
 

Cons

"The support is not very good. The team is not well-trained, and resolving a ticket can require several discussions."
"We are currently using version 7.3.1, but preferred the version before. The problem that we currently have is that Talend are releasing patches for Talend Studio every quarter. Our technical team has to be on top of these patches and constantly ensure everything is updated."
"Talend's architecture is complex to configure, especially due to the various components involved. It requires a more intricate setup."
"I would like to see better integration with other tools because every tool waiting for approval in terms of leveraging machine learning takes a long time."
"Deployment can be difficult, but I didn't test the latest version yet."
"Support is something that drives me crazy these days."
"Deployment can be difficult, but I didn't test the latest version yet. With Talend products, every release brings a lot of new features and functionalities. This is never a small adaptation, because the tool is maturing, but we need to test the latest version and to check its deployment capabilities."
"We encounter issues getting email notifications. They should provide enough information about the configuration process for email components."
"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
"There is room for improvement in query tuning."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."
 

Pricing and Cost Advice

"There are no additional licensing fees when you scale"
"There are multiple subscriptions available with Talend, each with its own scope. Subscriptions depend on the number of users you have and how many remote engines you want to install."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Comms Service Provider
13%
Computer Software Company
8%
Manufacturing Company
8%
Financial Services Firm
8%
Real Estate/Law Firm
14%
Manufacturing Company
14%
Retailer
12%
Construction Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise1
Large Enterprise3
No data available
 

Questions from the Community

What needs improvement with Talend Data Fabric?
One thing I found missing was integrations with SAP systems. We have extensively implemented one complex SAP project with Talend Data Fabric. At the same time, there were some complexities there, a...
What is your primary use case for Talend Data Fabric?
We are involved with multiple vendors, including Talend, Alteryx, and Informatica in the data management and governance space. In the classification and governance area, we use BigID, Spirion, and ...
What advice do you have for others considering Talend Data Fabric?
Initially, we were majorly using on-premise solutions and then we have moved into cloud deployments. It depends on the client and their requirement, whether they would want to go ahead with an on-p...
What is your experience regarding pricing and costs for Upsolver?
My experience with pricing, setup cost, and licensing is that the pricing is nine out of 10.
What needs improvement with Upsolver?
I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.
What is your primary use case for Upsolver?
My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...
 

Comparisons

 

Overview

Find out what your peers are saying about Talend Data Fabric vs. Upsolver and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.