We performed a comparison between Apache Spark Streaming and Confluent 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 solution is very stable and reliable."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"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."
"The solution is better than average and some of the valuable features include efficiency and stability."
"It's the fastest solution on the market with low latency data on data transformations."
"As an open-source solution, using it is basically free."
"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."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The solution can handle a high volume of data because it works and scales well."
"With Confluent Cloud we no longer need to handle the infrastructure and the plumbing, which is a concern for Confluent. The other advantage is that all portfolios have access to the data that is being shared."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."
"The monitoring module is impressive."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"We would like to have the ability to do arbitrary stateful functions in Python."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"In terms of improvement, the UI could be better."
"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 solution itself could be easier to use."
"It was resource-intensive, even for small-scale applications."
"The initial setup is quite complex."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"There is no local support team in Saudi Arabia."
"Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent."
"It could have more themes. They should also have more reporting-oriented plugins as well. It would be great to have free custom reports that can be dispatched directly from Jira."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"there is room for improvement in the visualization."
"The formatting aspect within the page can be improved and more powerful."
Apache Spark Streaming is ranked 8th in Streaming Analytics with 6 reviews while Confluent is ranked 3rd in Streaming Analytics with 11 reviews. Apache Spark Streaming is rated 8.0, while Confluent is rated 8.4. The top reviewer of Apache Spark Streaming writes "Easy deployment as a cluster and good documentation". On the other hand, the top reviewer of Confluent writes " a robust platform for real-time data streaming and event processing, enabling organizations to harness the power of real-time data for analytics and decision-making". Apache Spark Streaming is most compared with Amazon Kinesis, Azure Stream Analytics, Spring Cloud Data Flow, Apache Pulsar and Starburst Enterprise, whereas Confluent is most compared with Amazon MSK, Amazon Kinesis, AWS Glue, Databricks and Oracle GoldenGate. See our Apache Spark Streaming vs. Confluent report.
See our list of best Streaming Analytics vendors.
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