Apache Spark Streaming vs. Confluent Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark Streaming
Score 8.7 out of 10
N/A
Apache Spark Streaming is a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads.N/A
Confluent Platform
Score 7.5 out of 10
N/A
The Confluent Platform is an event streaming platform for enterprises from the company of same name in Mountain View, developed by the original developers of Apache Kafka.N/A
Pricing
Apache Spark StreamingConfluent Platform
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache Spark StreamingConfluent Platform
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache Spark StreamingConfluent Platform
Top Pros
Top Cons
Features
Apache Spark StreamingConfluent Platform
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Spark Streaming
8.4
1 Ratings
4% above category average
Confluent Platform
9.1
2 Ratings
12% above category average
Real-Time Data Analysis8.01 Ratings10.02 Ratings
Visualization Dashboards9.01 Ratings8.02 Ratings
Data Ingestion from Multiple Data Sources9.01 Ratings10.02 Ratings
Low Latency8.01 Ratings9.02 Ratings
Integrated Development Tools8.01 Ratings8.02 Ratings
Data wrangling and preparation8.01 Ratings00 Ratings
Linear Scale-Out8.01 Ratings9.02 Ratings
Machine Learning Automation9.01 Ratings00 Ratings
Data Enrichment9.01 Ratings10.01 Ratings
Best Alternatives
Apache Spark StreamingConfluent Platform
Small Businesses
Amazon Kinesis
Amazon Kinesis
Score 8.2 out of 10
Amazon Kinesis
Amazon Kinesis
Score 8.2 out of 10
Medium-sized Companies
Confluent Platform
Confluent Platform
Score 7.5 out of 10
Tealium Customer Data Hub
Tealium Customer Data Hub
Score 8.7 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 7.8 out of 10
Spotfire Streaming
Spotfire Streaming
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache Spark StreamingConfluent Platform
Likelihood to Recommend
9.0
(1 ratings)
10.0
(2 ratings)
Support Rating
-
(0 ratings)
10.0
(1 ratings)
User Testimonials
Apache Spark StreamingConfluent Platform
Likelihood to Recommend
Apache
Apache Spark Streaming is a tool that we are using for almost a year and is excellent in managing batch processing. It is user-friendly. Using it, we can even process our massive data in fractions of seconds. Its pricing is its other plus point. Only its In-memory processing is its demerit as it occupies a large memory.
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Confluent
If you have a need to stream data, real time or segmented structured data then Confluent is a great platform to do so with. You won't run into packet transfer size limitations that other platforms have. Flexibility in on-prem, cloud, and managed cloud offerings makes it very flexible no matter how you choose to implement.
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Pros
Apache
  • It is amazing in solving complicated transformative logic.
  • It is straightforward to program.
  • It is a very quick tool.
  • It processes large data within a fraction of seconds.
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Confluent
  • Products work great.
  • Training is available.
  • Customer support is good.
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Cons
Apache
  • There must be more documentation.
  • It is a profoundly complex tool.
  • Its in-memory processing consumes massive memory.
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Confluent
  • Cloud based Azure platform features for Confluent lacks behind AWS And GCP
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Support Rating
Apache
No answers on this topic
Confluent
The support from the Confluent platform is great and satisfying. We have been working with Confluent for more than a year now. They sent out resident architects to help us set up Confluent cluster on our cloud and help us troubleshoot problems we have encountered. Overall, it has been a great experience working with the Confluent Platform.
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Alternatives Considered
Apache
Apache Spark Streaming stands above all the huge data transformative tools because of its speed of processing which was quite slow in Presto as it takes a lot of our time in the data processing. Spark, comfortably provides integration with Jupyter like notebook environment. and Spark's combination with Jupyter and Python results in enhancing the speed .
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Confluent
For our use case it was very important that the technology we were working with fit into our Azure architecture, and met our data processing size requirements to stream data within certain SLAs. Confluent more than met our performance requirements and compared to the others scale options and cost to run it was more than financially viable as a platform solution to our global operations.
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Return on Investment
Apache
  • Cost and time-effective tool for our business.
  • We can integrate with Jupyter with many conveniences.
  • Its high-speed data processing has proved beneficial for us.
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Confluent
  • It enables us to develop event driven application.
  • It increases our ability to handle streaming data.
  • It reduces latency of communication.
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ScreenShots