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Coralogix 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

Coralogix
Ranking in Streaming Analytics
15th
Average Rating
8.4
Reviews Sentiment
6.6
Number of Reviews
13
Ranking in other categories
Application Performance Monitoring (APM) and Observability (21st), Log Management (21st), Security Information and Event Management (SIEM) (22nd), API Management (15th), Anomaly Detection Tools (1st), AI Observability (18th)
Upsolver
Ranking in Streaming Analytics
20th
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
3
Ranking in other categories
Data Integration (37th)
 

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Coralogix is 0.7%, up from 0.2% 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.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Coralogix0.7%
Upsolver0.7%
Other98.6%
Streaming Analytics
 

Featured Reviews

Naveenkumar Lakshman - PeerSpot reviewer
Presales Engineer at Crayon AS
Centralized monitoring has improved real-time issue tracking and reduced root cause analysis time
One of the best features that Coralogix offers is that it is integration friendly. I can seamlessly work with different cloud providers including AWS, Azure, and GCP. I can monitor Kubernetes or Docker platforms as well, and I can integrate with the DevOps chain including Jenkins and all infrastructure code, Terraform, or Ansible. Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool. I have the interface where I can use the drag-and-drop feature, and I can create different types of charts. Mainly, I have the line charts and time series ones that I generally use in many use cases, gauges, tables, pie charts, or markdown widgets. These are the ones generically available, and I can switch between the visualization types. I am getting the underlying query in that and can import and export dashboards built upon the JSON format. I can have my own APIs integrated with my dashboards as well, such as with Terraform, which is useful for scaling across my environments. Regarding root cause analysis, mainly what I can do is correlate across all of the layers because the main logs that I work on are storage-related, including CIFS, NFS, SAN traffic, and the metrics including storage, throughput, or VM resource usage. Being able to view logs, metrics, or traces available, I get all of these in one place, and I can do root cause analysis much quicker.
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

"For now, we have not experienced any stability issues."
"Coralogix scales well, and I will rate it nine out of ten."
"Coralogix has positively impacted my organization by providing a centralized console to monitor the dashboard, giving me rich flexibility to see different sorts of data that is spread across the logs, metrics, or traces, which are the typical pillars of the observability tool."
"The log monitoring is good, and the dashboards that we create are beneficial."
"Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams."
"The most valuable feature of Coralogix is that it is a very good vendor for metrics."
"In my experience, the best feature Coralogix offers is that the dashboard is pretty good."
"A non-tech person can easily get used to it."
"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."
"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

"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions."
"In terms of documentation, I think there can be more user-friendly documentation that stresses more on day-to-day issues."
"The user interface is not intuitive, especially when first onboarding, and improvements could be made here."
"The customizable dashboards haven't really helped with my company's efficiency at all, and I think there's room for improvement."
"The features we were missing in the past were related to the way we see our metrics and aggregate our data."
"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions. The increasing volume of data and the resulting bandwidth charges are concerns."
"The documentation of the tool could be improved"
"It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription."
"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."
"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."
 

Pricing and Cost Advice

"The cost of the solution is per volume of data ingested."
"The platform has a reasonable cost. I rate the pricing a three out of ten."
"We are paying roughly $5,000 a month."
"Currently, we are at a very minimal cost, which is around $400 per month since we have reduced our usage. Initially, we were at $900 per month."
"Upsolver is affordable at approximately $225 per terabyte per year."
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Top Industries

By visitors reading reviews
Financial Services Firm
10%
Computer Software Company
10%
Manufacturing Company
8%
Comms Service Provider
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise5
No data available
 

Questions from the Community

What do you like most about Coralogix?
Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams.
What is your experience regarding pricing and costs for Coralogix?
To monitor and manage costs associated with Coralogix, I analyze my trend, looking at how the data is being ingested. Generally, it is charged based on what we store, and therefore there are certai...
What needs improvement with Coralogix?
I think Coralogix can be improved with flexible dashboards. Creating specific views, such as saving a dev environment as a separate view rather than adding filters every time, would be great.
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....
 

Comparisons

 

Overview

 

Sample Customers

Payoneer, AGS, Monday.com, Capgemini
Information Not Available
Find out what your peers are saying about Coralogix vs. Upsolver and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.