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 better than average and some of the valuable features include efficiency and stability."
"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 very stable and reliable."
"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."
"As an open-source solution, using it is basically free."
"It's the fastest solution on the market with low latency data on data transformations."
"Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows."
"The design of the product is extremely well built and it is highly configurable."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"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."
"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."
"The documentation process is fast with the tool."
"It is also good for knowledge base management."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"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."
"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."
"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 solution itself could be easier to use."
"It was resource-intensive, even for small-scale applications."
"The initial setup is quite complex."
"We would like to have the ability to do arbitrary stateful functions in Python."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"The pricing model should include the ability to pick features and be charged for them only."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"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."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"There is a limitation when it comes to seamlessly importing Microsoft documents into Confluent pages, which can be inconvenient for users who frequently work with Microsoft Office tools and need to transition their content to Confluent."
"Confluent's price needs improvement."
Apache Spark Streaming is ranked 8th in Streaming Analytics with 8 reviews while Confluent is ranked 3rd in Streaming Analytics with 18 reviews. Apache Spark Streaming is rated 8.0, while Confluent 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 Confluent writes "Has good technical support services and a valuable feature for real-time data streaming ". 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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