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Coralogix vs Google Cloud Dataflow comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

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)
Google Cloud Dataflow
Ranking in Streaming Analytics
10th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
14
Ranking in other categories
No ranking in other categories
 

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 Google Cloud Dataflow is 4.5%, down from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Google Cloud Dataflow4.5%
Coralogix0.7%
Other94.8%
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.
Jana Polianskaja - PeerSpot reviewer
Data Engineer at Accenture
Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow
As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

Quotes from Members

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

Pros

"Coralogix scales well, and I will rate it nine out of ten."
"The log monitoring is good, and the dashboards that we create are beneficial."
"A non-tech person can easily get used to it."
"For now, we have not experienced any stability issues."
"The most valuable feature of Coralogix is that it is a very good vendor for metrics."
"The initial setup is straightforward."
"The overall stability and reliability of Coralogix are excellent, and I rarely encounter issues."
"The best feature of this solution allows us to correlate logs, metrics and traces."
"I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service."
"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."
"The solution allows us to program in any language we desire."
"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."
"The integration within Google Cloud Platform is very good."
"The service is relatively cheap compared to other batch-processing engines."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"Google's support team is good at resolving issues, especially with large data."
 

Cons

"It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription."
"The user interface is not intuitive, especially when first onboarding, and improvements could be made here."
"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 customizable dashboards haven't really helped with my company's efficiency at all, and I think there's room for improvement."
"From my experience, Coralogix has horrible Terraform providers."
"Maybe they could make it more user-friendly."
"The user interface could be more intuitive and explanatory."
"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions."
"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."
"The technical support has slight room for improvement."
"The authentication part of the product is an area of concern where improvements are required."
"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."
"They should do a market survey and then make improvements."
"The deployment time could also be reduced."
"The solution's setup process could be more accessible."
"Google Cloud Dataflow should include a little cost optimization."
 

Pricing and Cost Advice

"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."
"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."
"The solution is not very expensive."
"Google Cloud Dataflow is a cheap solution."
"The tool is cheap."
"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."
"The solution is cost-effective."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."
"Google Cloud is slightly cheaper than AWS."
"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."
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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%
Financial Services Firm
18%
Manufacturing Company
12%
Retailer
11%
Computer Software Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise2
Large Enterprise5
By reviewers
Company SizeCount
Small Business3
Midsize Enterprise2
Large Enterprise10
 

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 do you like most about Google Cloud Dataflow?
The product's installation process is easy...The tool's maintenance part is somewhat easy.
What is your experience regarding pricing and costs for Google Cloud Dataflow?
Pricing is normal. It is part of a package received from Google, and they are not charging us too high.
What needs improvement with Google Cloud Dataflow?
It can be improved in several ways. The system could function in an automated fashion and provide suggestions based on past transactions to achieve better scalability. Implementing AI-based suggest...
 

Also Known As

No data available
Google Dataflow
 

Overview

 

Sample Customers

Payoneer, AGS, Monday.com, Capgemini
Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
Find out what your peers are saying about Coralogix vs. Google Cloud Dataflow and other solutions. Updated: December 2025.
881,082 professionals have used our research since 2012.