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Matillion Data Productivity Cloud vs Upsolver comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 6, 2025

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

Matillion Data Productivity...
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
27
Ranking in other categories
Cloud Data Integration (8th)
Upsolver
Average Rating
8.6
Reviews Sentiment
7.6
Number of Reviews
2
Ranking in other categories
Data Integration (38th), Streaming Analytics (18th)
 

Mindshare comparison

While both are Data Integration and Access solutions, they serve different purposes. Matillion Data Productivity Cloud is designed for Cloud Data Integration and holds a mindshare of 3.4%, down 4.3% compared to last year.
Upsolver, on the other hand, focuses on Data Integration, holds 0.2% mindshare, up 0.0% since last year.
Cloud Data Integration
Data Integration
 

Featured Reviews

Tomáš Hronek - PeerSpot reviewer
Used for wrangling or transforming data from sources like S3 and Databricks
I use Matillion ETL for wrangling or transforming data from sources like S3 and Databricks The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation. Sometimes, we have issues with the solution's stability and need to restart it for…
Snehasish Das - PeerSpot reviewer
Allows for data to be moved across platforms and different data technologies
The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies. Upsolver does this in a quick time, unlike traditional processes which are time-consuming. Additionally, it offers scalability for large volumes of data, with performance and ease of cloud-native integration.

Quotes from Members

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

Pros

"The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple."
"The product's initial setup phase was easy."
"The product is quite stable and can handle complex data integration tasks well."
"Matillion ETL has great Git integration that is perfect and convenient to use."
"We allow non-technical people to use Matillion to load data into our data warehouse for reporting. Thus, it is easy enough to use that we don't always have to get a technical person involved in setting up a data movement (ETL)."
"The most valuable feature of Matillion ETL is the UI experience in which you can drag and drop most of the transformation."
"The product has a good user interface."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."
"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
 

Cons

"The improvement area could be possible if the tool provides better integration capabilities with other ecosystems, including governance tools or data cataloging tools, as it is currently an area where the solution is lacking."
"It can have multi-environment support. We should be able to deploy it in different environments. Its integration with SAP connection is not so nice, which should be improved. It can also support an on-prem database."
"Sometimes, we have issues with the solution's stability and need to restart it for three weeks or more."
"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."
"Going forward, I would like them to add custom jobs, since we still have to run these outside of Matillion."
"Performance can be improved for efficiency, and it can be made faster."
"Our main challenge currently is that Matillion runs on an EC2 instance, limiting us to running only two processes simultaneously at the entry level."
"I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly."
"There is room for improvement in query tuning."
"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."
"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

"The AWS pricing and licensing are a cost-effective solution for data integration needs."
"It is cost-effective. Based on our use case, it's efficient and cheap. It saves a lot of money and our upfront costs are less."
"The solution's pricing is not based on the licensing cost but on the running hours when the Matillion instance is up and running."
"The prices needs to be lower."
"It is not necessarily a cheap solution. However, it's reasonable priced, especially with the smaller machines that we run it on."
"It was procured through the AWS Marketplace because it keeps things simple. They offer retail-like checkout and bill through your existing Amazon Web Services account."
"Its price depends on what you expect. You pay on a monthly basis, but there is a possibility to have special contracts depending on the installation."
"A rough estimation of the cost is around 20,000 dollars a month, however, this is dependent on the machine used and how Matillion ETL is used."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Computer Software Company
15%
Manufacturing Company
9%
Energy/Utilities Company
5%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Matillion ETL?
The new version with the Productivity Cloud is very simple. It's easy to use, navigate, and understand.
What is your experience regarding pricing and costs for Matillion ETL?
While pricing can be an issue compared to other solutions, Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing c...
What needs improvement with Matillion ETL?
There are problems with GCP connectivity. Specifically, connections to BigQuery for extracting information are complex, and the optimization of the extraction process requires improvements. I raise...
What is your experience regarding pricing and costs for Upsolver?
Upsolver is affordable at approximately $225 per terabyte per year. Compared to what I know from others, it's cheaper than many other products.
What needs improvement with Upsolver?
There is room for improvement in query tuning. Upsolver could do a more in-depth analysis in employing machine power, such as CPU and memory, to enhance query performance. Furthermore, allocating C...
What is your primary use case for Upsolver?
I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs....
 

Also Known As

Matillion ETL for Redshift, Matillion ETL for Snowflake, Matillion ETL for BigQuery
No data available
 

Overview

 

Sample Customers

Thrive Market, MarketBot, PWC, Axtria, Field Nation, GE, Superdry, Quantcast, Lightbox, EDF Energy, Finn Air, IPRO, Twist, Penn National Gaming Inc
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