Apache Kafka vs. Confluent

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Kafka
Score 8.4 out of 10
N/A
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.N/A
Confluent
Score 7.4 out of 10
N/A
Confluent Cloud is a cloud-native service for Apache Kafka used to connect and process data in real time with a fully managed data streaming platform. Confluent Platform is the self-managed version.N/A
Pricing
Apache KafkaConfluent
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache KafkaConfluent
Free Trial
NoYes
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 KafkaConfluent
Considered Both Products
Apache Kafka
Chose Apache Kafka
Confluent Cloud is still based on Apache Kafka but it has a subscription fee so, from a long term perspective, it is wiser to deploy your own Kafka instance that spans public and private cloud. Amazon Kinesis, Google Cloud Pub/Sub do not do well for a very number of messages …
Confluent
Chose 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 …
Top Pros
Top Cons
Features
Apache KafkaConfluent
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Kafka
-
Ratings
Confluent
9.1
2 Ratings
12% above category average
Real-Time Data Analysis00 Ratings10.02 Ratings
Visualization Dashboards00 Ratings8.02 Ratings
Data Ingestion from Multiple Data Sources00 Ratings10.02 Ratings
Low Latency00 Ratings9.02 Ratings
Integrated Development Tools00 Ratings8.02 Ratings
Linear Scale-Out00 Ratings9.02 Ratings
Data Enrichment00 Ratings10.01 Ratings
Best Alternatives
Apache KafkaConfluent
Small Businesses

No answers on this topic

IBM Streams
IBM Streams
Score 9.0 out of 10
Medium-sized Companies
IBM MQ
IBM MQ
Score 9.0 out of 10
Tealium Customer Data Hub
Tealium Customer Data Hub
Score 8.7 out of 10
Enterprises
IBM MQ
IBM MQ
Score 9.0 out of 10
Spotfire Streaming
Spotfire Streaming
Score 8.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache KafkaConfluent
Likelihood to Recommend
8.3
(18 ratings)
10.0
(2 ratings)
Likelihood to Renew
9.0
(2 ratings)
-
(0 ratings)
Usability
10.0
(1 ratings)
-
(0 ratings)
Support Rating
8.4
(4 ratings)
10.0
(1 ratings)
User Testimonials
Apache KafkaConfluent
Likelihood to Recommend
Apache
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.
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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
  • Really easy to configure. I've used other message brokers such as RabbitMQ and compared to them, Kafka's configurations are very easy to understand and tweak.
  • Very scalable: easily configured to run on multiple nodes allowing for ease of parallelism (assuming your queues/topics don't have to be consumed in the exact same order the messages were delivered)
  • Not exactly a feature, but I trust Kafka will be around for at least another decade because active development has continued to be strong and there's a lot of financial backing from Confluent and LinkedIn, and probably many other companies who are using it (which, anecdotally, is many).
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Confluent
  • Products work great.
  • Training is available.
  • Customer support is good.
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Cons
Apache
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
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Confluent
  • Cloud based Azure platform features for Confluent lacks behind AWS And GCP
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Likelihood to Renew
Apache
Kafka is quickly becoming core product of the organization, indeed it is replacing older messaging systems. No better alternatives found yet
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Confluent
No answers on this topic
Usability
Apache
Apache Kafka is highly recommended to develop loosely coupled, real-time processing applications. Also, Apache Kafka provides property based configuration. Producer, Consumer and broker contain their own separate property file
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Confluent
No answers on this topic
Support Rating
Apache
Support for Apache Kafka (if willing to pay) is available from Confluent that includes the same time that created Kafka at Linkedin so they know this software in and out. Moreover, Apache Kafka is well known and best practices documents and deployment scenarios are easily available for download. For example, from eBay, Linkedin, Uber, and NYTimes.
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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
I used other messaging/queue solutions that are a lot more basic than Confluent Kafka, as well as another solution that is no longer in the market called Xively, which was bought and "buried" by Google. In comparison, these solutions offer way fewer functionalities and respond to other needs.
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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
  • Positive: Get a quick and reliable pub/sub model implemented - data across components flows easily.
  • Positive: it's scalable so we can develop small and scale for real-world scenarios
  • Negative: it's easy to get into a confusing situation if you are not experienced yet or something strange has happened (rare, but it does). Troubleshooting such situations can take time and effort.
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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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