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Apache Flink vs. Confluent

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Flink
Score 9.0 out of 10
N/A
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. And FlinkCEP is the Complex Event Processing (CEP) library implemented on top of Flink. Users can detect event patterns in streams of events.N/A
Confluent
Score 9.9 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.
$0
Pricing
Apache FlinkConfluent
Editions & Modules
No answers on this topic
Basic
$0
Standard
Starting at ~$385
per month
Enterprise
Starting at ~$1,150
per month
Offerings
Pricing Offerings
Apache FlinkConfluent
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details—Confluent monthly bills are based upon resource consumption, i.e., you are only charged for the resources you use when you actually use them: Stream: Kafka clusters are billed for eCKUs/CKUs ($/hour), networking ($/GB), and storage ($/GB-hour). Connect: Use of connectors is billed based on throughput ($/GB) and a task base price ($/task/hour). Process: Use of stream processing with Confluent Cloud for Apache Flink is calculated based on CFUs ($/minute). Govern: Use of Stream Governance is billed based on environment ($/hour). Confluent storage and throughput is calculated in binary gigabytes (GB), where 1 GB is 2^30 bytes. This unit of measurement is also known as a gibibyte (GiB). Please also note that all prices are stated in United States Dollars unless specifically stated otherwise. All billing computations are conducted in Coordinated Universal Time (UTC).
More Pricing Information
Community Pulse
Apache FlinkConfluent
Considered Both Products
Apache Flink
Verified User
Anonymous
Chose Apache Flink
Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and …
Confluent
Verified User
Anonymous
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 …
Verified User
Anonymous
Chose Confluent
We chose to use the Confluent Platform because they provide enterprise-grade customer service support. Whenever we have trouble setting up or using the service, we can create a ticket for them and it will be resolved pretty fast. Kafka is the open-source software that comes …
Features
Apache FlinkConfluent
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Flink
8.7
Ratings
8% above category average
Confluent
9.1
Ratings
13% above category average
Real-Time Data Analysis10.00 Ratings10.00 Ratings
Data Ingestion from Multiple Data Sources7.00 Ratings10.00 Ratings
Low Latency10.00 Ratings9.00 Ratings
Data wrangling and preparation6.00 Ratings00 Ratings
Linear Scale-Out9.00 Ratings9.00 Ratings
Data Enrichment10.00 Ratings10.00 Ratings
Visualization Dashboards00 Ratings8.00 Ratings
Integrated Development Tools00 Ratings8.00 Ratings
Best Alternatives
Apache FlinkConfluent
Small Businesses
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
Medium-sized Companies
Confluent
Confluent
Score 9.9 out of 10
Tealium Customer Data Hub
Tealium Customer Data Hub
Score 8.2 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache FlinkConfluent
Likelihood to Recommend
9.0
(0 ratings)
10.0
(0 ratings)
Support Rating
-
(0 ratings)
10.0
(0 ratings)
User Testimonials
Apache FlinkConfluent
Likelihood to Recommend
In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.
Verified User
Anonymous
Read full review
If your company needs to build event-driven applications, like in healthcare industry, you need to enhance interoperability, and you are seeking a reliable service with enterprise-grade support, Confluent is the best on the market you can get. Their product works great and they provide very good customer service.
Verified User
Anonymous
Read full review
Pros
  • Low latency Stream Processing, enabling real-time analytics
  • Scalability, due its great parallel capabilities
  • Stateful Processing, providing several built-in fault tolerance systems
  • Flexibility, supporting both batch and stream processing
Verified User
Anonymous
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  • Products work great.
  • Training is available.
  • Customer support is good.
Verified User
Anonymous
Read full review
Cons
  • Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
  • Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
  • Community smaller than other frameworks
Verified User
Anonymous
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  • Cloud based Azure platform features for Confluent lacks behind AWS And GCP
Verified User
Anonymous
Read full review
Support Rating
No answers on this topic
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.
Verified User
Anonymous
Read full review
Alternatives Considered
Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.
Verified User
Anonymous
Read full review
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.
Verified User
Anonymous
Read full review
Return on Investment
  • Allowed for real-time data recovery, adding significant value to the busines
  • Enabled us to create new internal tools that we couldn't find in the market, becoming a strategic asset for the business
  • Enhanced the overall technical capability of the team
Verified User
Anonymous
Read full review
  • Confluent replaced Microsoft Event Hubs in our environment and unblocked data platform services rollout globally.
Verified User
Anonymous
Read full review
ScreenShots