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."
"As an open-source solution, using it is basically free."
"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."
"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."
"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."
"One of the best features of Confluent is that it's very easy to search and have a live status with Jira."
"The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka."
"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 design of the product is extremely well built and it is highly configurable."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The documentation process is fast with the tool."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"Their tech support is amazing; they are very good, both on and off-site."
"The initial setup is quite complex."
"In terms of improvement, the UI could be better."
"The solution itself could be easier to use."
"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."
"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."
"It was resource-intensive, even for small-scale applications."
"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 could have more integration with different platforms."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"The pricing model should include the ability to pick features and be charged for them only."
"there is room for improvement in the visualization."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"They should remove Zookeeper because of security issues."
"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."
"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 19 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, Databricks, AWS Glue and Oracle GoldenGate. See our Apache Spark Streaming vs. Confluent 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.