We performed a comparison between Coralogix and Google Cloud Dataflow based on real PeerSpot user reviews.
Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The initial setup is straightforward."
"The best feature of this solution allows us to correlate logs, metrics and traces."
"A non-tech person can easily get used to it."
"The solution offers very good convenience filtering."
"The solution is easy to use and to start with."
"Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams."
"It is a scalable solution."
"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."
"The product's installation process is easy...The tool's maintenance part is somewhat easy."
"The most valuable features of Google Cloud Dataflow are scalability and connectivity."
"The support team is good and it's easy to use."
"Google Cloud Dataflow is useful for streaming and data pipelines."
"From my experience, Coralogix has horrible Terraform providers."
"The documentation of the tool could be improved"
"The user interface could be more intuitive and explanatory."
"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."
"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."
"Google Cloud Dataflow should include a little cost optimization."
"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."
"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."
"They should do a market survey and then make improvements."
"The technical support has slight room for improvement."
"There are certain challenges regarding the Google Cloud Composer which can be improved."
"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."
"The authentication part of the product is an area of concern where improvements are required."
Coralogix is ranked 11th in Streaming Analytics with 7 reviews while Google Cloud Dataflow is ranked 7th in Streaming Analytics with 10 reviews. Coralogix is rated 8.4, while Google Cloud Dataflow is rated 7.8. The top reviewer of Coralogix writes "Good capabilities, has a helpful interface and is straightforward to set up". On the other hand, the top reviewer of Google Cloud Dataflow writes "Easy to use for programmers, user-friendly, and scalable". Coralogix is most compared with Datadog, Grafana, Sentry, New Relic and Elastic Search, whereas Google Cloud Dataflow is most compared with Databricks, Apache NiFi, Amazon MSK, Amazon Kinesis and Spring Cloud Data Flow. See our Coralogix vs. Google Cloud Dataflow report.
See our list of best Streaming Analytics vendors.
We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
