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Axiom Team vs Stackify 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

Axiom Team
Ranking in Log Management
42nd
Average Rating
8.6
Number of Reviews
2
Ranking in other categories
Data Observability (9th)
Stackify
Ranking in Log Management
58th
Average Rating
7.8
Number of Reviews
6
Ranking in other categories
Application Performance Monitoring (APM) and Observability (64th), IT Infrastructure Monitoring (65th)
 

Mindshare comparison

As of April 2026, in the Log Management category, the mindshare of Axiom Team is 0.3%. The mindshare of Stackify is 0.7%, up from 0.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Log Management Mindshare Distribution
ProductMindshare (%)
Axiom Team0.3%
Stackify0.7%
Other99.0%
Log Management
 

Featured Reviews

reviewer2783832 - PeerSpot reviewer
Programmer 1 at a manufacturing company with 10,001+ employees
Logging has reduced costs and now provides fast queries and dashboards for lambda troubleshooting
Axiom Team excels at querying, with a query language that makes it very easy to assemble queries. The platform also makes it simple to create dashboards from logs. Axiom Team dashboards are used to monitor execution time, pricing, and errors. Axiom Team has positively impacted the organization by greatly reducing logging costs.
IE
Senior Software Engineer at a tech services company with 1,001-5,000 employees
Has good filtering and rating features and helps with resource and load management
I've not used Stackify for a while, and I'm currently using a solution now that's not as good as Stackify. Among the solutions I've been using so far, Stackify has been one of the best for me, but there's always room for improvement. For example, I don't know if it's just me, but when I try to get the log from Stackify, sometimes it doesn't appear in real-time. It takes a few minutes before the logs appear. When I redeploy my solution and the application starts, I don't see the logs immediately, and it would take two to three minutes before I see the logs. I don't know if other customers have a similar experience. It's the wait time for the logs to appear that's a concern for me, could be improved, and is what the Stackify team should be looking into. In terms of any additional feature that I'd like added to the solution, I'm not sure if Stackify has a way to export logs out. I've been trying to do it. On the solution, you can click on a spiral-like icon and it shows you the entire error, and I'd prefer an export button that would let me download the error and save that into a text file, for example, so it'll be available on my local machine for me to reference it, especially because the log keeps going and as you're using the solution, the system keeps pushing messages on to Stackify, so if I'm looking at a particular error at 12:05 PM, for example, by the time I go back to my system and would like to revisit the error at 12:25 PM, on Stackify, the logs would have gone past that level and I won't see it again which makes it difficult. When you now go back to that timestamp, you don't tend to see it immediately, but if the solution had an export feature for me to save that particular error information on my local machine for reference at a later time, I won't have to go back to Stackify. I just go to that log, specifically to that particular export that I've received on my local machine. I can get it and review it, and it would be easier that way versus me going back to Stackify to find that particular error and request that particular information.

Quotes from Members

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

Pros

"Axiom Team has positively impacted my organization mainly in terms of cost, as we have reduced our logging cost by approximately half."
"Axiom Team has positively impacted the organization by greatly reducing logging costs."
"What stood out to us were the metrics and granular details we received."
"We switched from New Relic and Loggly as it provides us more info at a lower price."
"The performance dashboard and the accurate level of details are beneficial."
"The deployment is very fast."
"The solution is stable and reliable."
"Within few hours of install we've identify the source of issue we've been investigating for few days and couldn't pin point."
"The filter feature on Stackify is one of the features I found valuable. It's awesome. When I want to get the application logs, the solution gives me many filters. For example, if I want to get logs from my test environment, the option is there for me to select the environment from Stackify, and you can also select the particular application, and you'll see the information you need there. The filter feature alone and the fact that Stackify offers a lot of different filters is what I like the most about the solution because I've used other tools with the filter feature, but the filtering was very difficult, versus Stackify that has good filtering. On Stackify, you can filter the information by the last one hour, or the last four hours, and you can also select the date range and specify the timestamp, then the solution will give you the information based on the date range you specified. Another feature I found valuable on Stackify is its rating feature because it tells you how your application is faring. For example, a rating of A means excellent, while a rating of F means very bad, or that your application is not doing well at all. The ratings are from A to F. I also like that Stackify helps you in terms of load management because the solution gives you information on overutilized resources. These are the most valuable features of the solution."
"The solution is stable and reliable."
 

Cons

"Axiom Team can be improved by ingesting logs faster, if possible."
"The search feature could be improved."
"I'm looking to see more performance tools, but heard that they are going to release some."
"Better mobile support."
"Another improvement would be the agent memory utilization, which led to our recent reevaluation."
"When I redeploy my solution and the application starts, I don't see the logs immediately, and it would take two to three minutes before I see the logs."
"I've not used Stackify for a while, and I'm currently using a solution now that's not as good as Stackify. Among the solutions I've been using so far, Stackify has been one of the best for me, but there's always room for improvement. For example, I don't know if it's just me, but when I try to get the log from Stackify, sometimes it doesn't appear in real-time. It takes a few minutes before the logs appear. When I redeploy my solution and the application starts, I don't see the logs immediately, and it would take two to three minutes before I see the logs. I don't know if other customers have a similar experience. It's the wait time for the logs to appear that's a concern for me, could be improved, and is what the Stackify team should be looking into. In terms of any additional feature that I'd like added to the solution, I'm not sure if Stackify has a way to export logs out. I've been trying to do it. On the solution, you can click on a spiral-like icon and it shows you the entire error, and I'd prefer an export button that would let me download the error and save that into a text file, for example, so it'll be available on my local machine for me to reference it, especially because the log keeps going and as you're using the solution, the system keeps pushing messages on to Stackify, so if I'm looking at a particular error at 12:05 PM, for example, by the time I go back to my system and would like to revisit the error at 12:25 PM, on Stackify, the logs would have gone past that level and I won't see it again which makes it difficult. When you now go back to that timestamp, you don't tend to see it immediately, but if the solution had an export feature for me to save that particular error information on my local machine for reference at a later time, I won't have to go back to Stackify. I just go to that log, specifically to that particular export that I've received on my local machine. I can get it and review it, and it would be easier that way versus me going back to Stackify to find that particular error and request that particular information."
"I would like to be able to see metrics about individual running containers on the host machines."
"It's not easy to set up. It's hard especially for juniors to understand."
 

Pricing and Cost Advice

Information not available
"The price is variable. It depends on how much data we have received in that particular month. Usually, it goes up to $2,000, or, at times, $3,000 USD per month."
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Top Industries

By visitors reading reviews
Construction Company
34%
Comms Service Provider
10%
Financial Services Firm
8%
Transportation Company
8%
Construction Company
18%
Comms Service Provider
13%
Media Company
8%
Performing Arts
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise2
 

Questions from the Community

What is your experience regarding pricing and costs for Axiom Team?
Pricing, setup cost, and licensing experience are not available due to lack of access to billing information.
What needs improvement with Axiom Team?
Axiom Team can be improved by ingesting logs faster, if possible.
What is your primary use case for Axiom Team?
Axiom Team is primarily used for logging Lambda functions and searching through those logs. When issues arise, the function logs are examined to determine what went wrong, and Axiom Team effectivel...
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Comparisons

 

Overview

 

Sample Customers

Information Not Available
MyRacePass, ClearSale, Newitts, Carbonite, Boston Software, Children's International, Starkwood Media Group, Fewzion
Find out what your peers are saying about Axiom Team vs. Stackify and other solutions. Updated: April 2026.
886,858 professionals have used our research since 2012.