We performed a comparison between Apache Flink and Coralogix 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 documentation is very good."
"The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis."
"The product helps us to create both simple and complex data processing tasks. Over time, it has facilitated integration and navigation across multiple data sources tailored to each client's needs. We use Apache Flink to control our clients' installations."
"Apache Flink allows you to reduce latency and process data in real-time, making it ideal for such scenarios."
"It is user-friendly and the reporting is good."
"Apache Flink is meant for low latency applications. You take one event opposite if you want to maintain a certain state. When another event comes and you want to associate those events together, in-memory state management was a key feature for us."
"Apache Flink's best feature is its data streaming tool."
"With Flink, it provides out-of-the-box checkpointing and state management. It helps us in that way. When Storm used to restart, sometimes we would lose messages. With Flink, it provides guaranteed message processing, which helped us. It also helped us with maintenance or restarts."
"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."
"Numerous data monitoring tools are available, but Coralogix somehow fine-tunes our policies and effectively supports our teams."
"The solution is easy to use and to start with."
"The solution offers very good convenience filtering."
"Amazon's CloudFormation templates don't allow for direct deployment in the private subnet."
"In terms of stability with Flink, it is something that you have to deal with every time. Stability is the number one problem that we have seen with Flink, and it really depends on the kind of problem that you're trying to solve."
"There is a learning curve. It takes time to learn."
"In terms of improvement, there should be better reporting. You can integrate with reporting solutions but Flink doesn't offer it themselves."
"PyFlink is not as fully featured as Python itself, so there are some limitations to what you can do with it."
"In a future release, they could improve on making the error descriptions more clear."
"Apache Flink should improve its data capability and data migration."
"We have a machine learning team that works with Python, but Apache Flink does not have full support for the language."
"From my experience, Coralogix has horrible Terraform providers."
"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."
"The user interface could be more intuitive and explanatory."
"Maybe they could make it more user-friendly."
"It would be helpful if Coralogix could integrate the main modules that any organization requires into a single subscription."
"The documentation of the tool could be improved"
Apache Flink is ranked 5th in Streaming Analytics with 15 reviews while Coralogix is ranked 11th in Streaming Analytics with 7 reviews. Apache Flink is rated 7.6, while Coralogix is rated 8.4. The top reviewer of Apache Flink writes "A great solution with an intricate system and allows for batch data processing". On the other hand, the top reviewer of Coralogix writes "Good capabilities, has a helpful interface and is straightforward to set up". Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Databricks, Azure Stream Analytics and Apache Pulsar, whereas Coralogix is most compared with Datadog, Grafana, Sentry, New Relic and Elastic Search. See our Apache Flink vs. Coralogix report.
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