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Census vs Upsolver comparison

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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

Census
Ranking in Data Integration
44th
Average Rating
8.6
Reviews Sentiment
5.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
Upsolver
Ranking in Data Integration
41st
Average Rating
8.6
Reviews Sentiment
7.6
Number of Reviews
4
Ranking in other categories
Streaming Analytics (22nd)
 

Mindshare comparison

As of November 2026, in the Data Integration category, the mindshare of Census is 0.4%, down from 0.4% compared to the previous year. The mindshare of Upsolver is 0.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Upsolver0.7%
Census0.4%
Other98.9%
Data Integration
 

Featured Reviews

reviewer2784462 - PeerSpot reviewer
Software Engineer at a tech vendor with 10,001+ employees
Data activation has become faster and business teams access consistent customer insights
Census has been very useful to us as a reverse ETL layer. We have reduced engineering efforts, which has translated into tens of thousands of euros per year in avoided development and maintenance costs, faster and more accurate customer activation, and other improvements that we achieved using Census. Census is faster than our previous approach. Census has enabled faster activation of analytic data into CRM and marketing platforms in our case. Another key benefit is the elimination of manual exports and custom integration scripts, consistent customer data across analytical and operational systems. The best feature that Census offers is that it works directly on top of the data warehouse, preserving a single source of truth. Another valuable feature is that Census provides excellent support for CRM, marketing, and customer-facing platforms. Census creates a single source of truth by making the data warehouse the only place where business logic and data definition live and by ensuring that all downstream operational systems are consumers, not owners of data. All customer attributes, metrics, and segments are defined once, directly in the data warehouse, using SQL and existing data models. Census was useful for us because of the fast time to value, as new syncs can be configured and deployed quickly without custom development. It also ensures that data models are clean and well-defined in the data warehouse after we start using Census. Based on delivery metrics and team feedback, the benefit is that the time to activate new use cases was reduced from weeks to days. Engineering effort dedicated to reverse ETL pipelines decreased by sixty to seventy percent. Maintenance overhead for custom integration was almost completely eliminated, and marketing and growth teams accelerated experimentation cycles significantly. From a cost perspective, reduced engineering effort translated into tens of thousands of euros per year in avoided development and maintenance costs, and faster and more accurate customer activation improved campaign effectiveness and business responsiveness.
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

"Based on delivery metrics and team feedback, the benefit is that the time to activate new use cases was reduced from weeks to days, engineering effort dedicated to reverse ETL pipelines decreased by sixty to seventy percent, maintenance overhead for custom integration was almost completely eliminated, and marketing and growth teams accelerated experimentation cycles significantly."
"The catalog of connectors and the integration with dbt have made my daily work easier because, regarding the number of connectors available, there are two hundred or more connectors, so it is difficult to have a destination that does not work for you, and using the integration with dbt allows me to reuse analytical models I already have."
"Reverse ETL makes warehouse data more accessible to business teams, saves repetitive work, and helps improve the consistency of customer information across platforms."
"Customer service is excellent, and I would rate it between eight point five to nine out of ten."
"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."
"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."
"I have saved 50 to 60% on maintaining pipelines since using Upsolver."
 

Cons

"I would like to see more advanced data quality checks, clearer error messages when a sync fails, and easier troubleshooting for complex workflows."
"The areas for improvement are complex transformation logic because it must still be handled upstream in the warehouse, and cost predictability requires attention at high data volumes."
"I think Census could be improved by offering some advanced custom configurations or complex mappings that may have a higher learning curve, and the cost forecasting at large scale sometimes requires too much attention, and the information provided about it could be improved."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
"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."
"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."
"There is room for improvement in query tuning."
"I would say Upsolver's scalability is eight out of 10 because of pricing."
 

Pricing and Cost Advice

Information not available
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Manufacturing Company
11%
Financial Services Firm
11%
Construction Company
9%
Comms Service Provider
9%
Real Estate/Law Firm
13%
Manufacturing Company
13%
Retailer
12%
Comms Service Provider
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What needs improvement with Census?
Census has been performing very well overall. One area that may need improvement is that sometimes a custom setup is very difficult to configure. This was the case with our Intercom segment setup. ...
What is your primary use case for Census?
Census is a versatile data synchronizing solution that solves a wide range of data management problems for our business. With Census, we were able to reduce the sync time taken to transfer data fro...
What advice do you have for others considering Census?
I would rate Census an eight out of ten according to my experience. I feel it is not quite a ten because sometimes a custom setup is very difficult to configure. This was the case with our Intercom...
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 Census vs. Upsolver and other solutions. Updated: November 2026.
921,523 professionals have used our research since 2012.