Coralogix vs Google Cloud Dataflow comparison

Coralogix and Google are both solutions in the Streaming Analytics category. Coralogix is ranked #12 with an average rating of 8.2, while Google is ranked #7 with an average rating of 8.1. Coralogix holds a 0.2% mindshare in SA, compared to Google’s 6.8% mindshare. Additionally, 92% of Coralogix users are willing to recommend the solution, compared to 92% of Google users who would recommend it.

Coralogix

Read 11 Coralogix reviews

51 Views
29 Comparison Views

92% willing to recommend

Google Cloud Dataflow

Read 13 Google Cloud Dataflow reviews

2,758 Views
1,111 Comparison Views

92% willing to recommend

Coralogix

Google Cloud Dataflow

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 17, 2024

Google Cloud Dataflow and Coralogix compete in the data management ecosystem, focusing on real-time data processing and log analytics, respectively. Dataflow holds the upper hand due to its scalability and pricing advantages, while Coralogix offers feature adaptability.

Features: Google Cloud Dataflow provides robust real-time data processing, excellent integration with Google Cloud services, and efficient batch and stream pipeline management. Coralogix offers comprehensive log analytics, seamless integration capabilities, and extensive alerting functionality.

Room for Improvement: Google Cloud Dataflow could enhance logging configuration complexity, expand its support for non-Google ecosystems, and offer more cost transparency. Coralogix may improve by simplifying deployment, reducing perceived pricing for smaller use cases, and enhancing initial setup documentation.

Ease of Deployment and Customer Service: Google Cloud Dataflow benefits from straightforward deployment and extensive documentation support, facilitating setup within Google's infrastructure. Coralogix provides ease of integration with personalized customer service, though deployment requires understanding complex logging configurations.

Pricing and ROI: Google Cloud Dataflow presents competitive pricing aligned with Google’s ecosystem, demonstrating significant ROI in large-scale tasks. Coralogix's pricing reflects its comprehensive logging features but can seem high for smaller implementations, though it delivers high ROI through versatile analytics.

To learn more, read our detailed Coralogix vs. Google Cloud Dataflow Report (Updated: June 2025).

Buyer's Guide

Coralogix vs. Google Cloud Dataflow

June 2025

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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

12th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (20th), Log Management (19th), Security Information and Event Management (SIEM) (22nd), API Management (16th), Anomaly Detection Tools (1st)

Google Cloud Dataflow

Ranking in Streaming Analytics

7th

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Streaming Analytics category, the mindshare of Coralogix is 0.2%, up from 0.1% compared to the previous year. The mindshare of Google Cloud Dataflow is 6.8%, down from 7.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

reviewer1915599

VP of Engineering at a financial services firm with 51-200 employees

Good capabilities, has a helpful interface and is straightforward to set up

We have asked for a couple of features from the company already. What typically happens is a lot of people - and developers are one of the biggest consumers of this product - go to this product to optimize their investigation process and specific configurations. That increases our data flow at times, so the cost changes. And a lot of changes happen due to that. We have asked the company to auto-revert the changes after a while so that the system works typically. We want it to work at what it is expected to work at and not really based on the updated configuration which one developer has decided to change.

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Jana Polianskaja

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.

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Quotes from Members

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

Pros

"Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams."

"The best feature of this solution allows us to correlate logs, metrics and traces."

"The initial setup is straightforward."

"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."

"The solution is easy to use and to start with."

"For now, we have not experienced any stability issues."

"A non-tech person can easily get used to it."

More Coralogix pros

"I would rate the overall solution a ten out of ten."

"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 best feature of Google Cloud Dataflow is its practical connectedness."

"It allows me to test solutions locally using runners like Direct Runner without having to start a Dataflow job, which can be costly."

"The product's installation process is easy...The tool's maintenance part is somewhat easy."

"The support team is good and it's easy to use."

"The solution allows us to program in any language we desire."

"The integration within Google Cloud Platform is very good."

More Google Cloud Dataflow pros

Cons

"The features we were missing in the past were related to the way we see our metrics and aggregate our data."

"From my experience, Coralogix has horrible Terraform providers."

"The user interface could be more intuitive and explanatory."

"It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription."

"Maybe they could make it more user-friendly."

"The documentation of the tool could be improved"

"The customizable dashboards haven't really helped with my company's efficiency at all, and I think there's room for improvement."

"Coralogix should have some AI capabilities to auto-detect anomalies and provide suggestions."

More Coralogix cons

"The authentication part of the product is an area of concern where improvements are required."

"Occasionally, dealing with a huge volume of data causes failure due to array size."

"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."

"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."

"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."

"Promoting the technology more broadly would help increase its adoption."

"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."

More Google Cloud Dataflow cons

Pricing and Cost Advice

"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."

"We are paying roughly $5,000 a month."

"The platform has a reasonable cost. I rate the pricing a three out of ten."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"The tool is cheap."

"Google Cloud is slightly cheaper than AWS."

"The solution is not very expensive."

"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."

"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."

"Google Cloud Dataflow is a cheap solution."

"The solution is cost-effective."

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Top Industries

By visitors reading reviews

Computer Software Company

13%

Financial Services Firm

11%

Manufacturing Company

Healthcare Company

Financial Services Firm

18%

Manufacturing Company

12%

Retailer

11%

Computer Software Company

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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.

See all answers

What is your experience regarding pricing and costs for Coralogix?

The pricing is expensive. We need to reduce logs to manage costs. Despite the expense, I believe it is worth the money to have Coralogix as a tool.

See all answers

What needs improvement with Coralogix?

Change might not be the correct word, but with every service, there is always room to improve. They are improving their services daily and deploy new features. When we had missing features that we ...

See all answers

What do you like most about Google Cloud Dataflow?

The product's installation process is easy...The tool's maintenance part is somewhat easy.

See all answers

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.

See all answers

What needs improvement with Google Cloud Dataflow?

I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...

See all answers

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Compared 12% of the time

Amazon MSK vs Google Cloud Dataflow

Compared 9% of the time

Spring Cloud Data Flow vs Google Cloud Dataflow

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Product Reports

Buyer's Guide

Coralogix

June 2025

Download Coralogix product report

Buyer's Guide

Google Cloud Dataflow

June 2025

Download Google Cloud Dataflow product report

Also Known As

No data available

Google Dataflow

Overview

Coralogix is a stateful streaming data platform that provides real-time insights and long-term trend analysis with no reliance on storage or indexing, solving the monitoring challenges of data growth in large-scale systems.

Ingest log, metric, and security data from any source for a single, centralized platform to monitor and alert on your applications. As data is ingested, Coralogix instantly narrows millions of events down to common patterns for deeper insights and faster troubleshooting. Proactive data storage optimization enables up to 70% savings on monitoring costs with better performance.

Coralogix

Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Google

Sample Customers

Payoneer, AGS, Monday.com, Capgemini

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale

Buyer's Guide

Coralogix vs. Google Cloud Dataflow

June 2025

Free Report: Coralogix vs. Google Cloud Dataflow

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