We performed a comparison between Apache Spark Streaming 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."Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."
"The solution is better than average and some of the valuable features include efficiency and stability."
"As an open-source solution, using it is basically free."
"The solution is very stable and reliable."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"It's the fastest solution on the market with low latency data on data transformations."
"The initial setup is straightforward."
"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 best feature of this solution allows us to correlate logs, metrics and traces."
"The solution offers very good convenience filtering."
"We would like to have the ability to do arbitrary stateful functions in Python."
"In terms of improvement, the UI could be better."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better."
"The initial setup is quite complex."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"It was resource-intensive, even for small-scale applications."
"The solution itself could be easier to use."
"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."
"Maybe they could make it more user-friendly."
"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."
Apache Spark Streaming is ranked 8th in Streaming Analytics with 8 reviews while Coralogix is ranked 11th in Streaming Analytics with 7 reviews. Apache Spark Streaming is rated 8.0, while Coralogix is rated 8.4. The top reviewer of Apache Spark Streaming writes "Easy integration, beneficial auto-scaling, and good open-sourced support community". On the other hand, the top reviewer of Coralogix writes "Good capabilities, has a helpful interface and is straightforward to set up". Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Confluent and Apache Pulsar, whereas Coralogix is most compared with Datadog, Grafana, Sentry, New Relic and Elastic Search. See our Apache Spark Streaming vs. Coralogix report.
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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.
