Apache Flink vs. Oracle Stream Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Flink
Score 9.2 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
Oracle Stream Analytics
Score 0.0 out of 10
N/A
Oracle supports streaming analytics needs with Oracle Stream Analytics, currently in its 18th edition.N/A
Pricing
Apache FlinkOracle Stream Analytics
Editions & Modules
No answers on this topic
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Offerings
Pricing Offerings
Apache FlinkOracle Stream Analytics
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 FlinkOracle Stream Analytics
Top Pros

No answers on this topic

Top Cons

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Features
Apache FlinkOracle Stream Analytics
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Flink
8.7
1 Ratings
7% above category average
Oracle Stream Analytics
-
Ratings
Real-Time Data Analysis10.01 Ratings00 Ratings
Data Ingestion from Multiple Data Sources7.01 Ratings00 Ratings
Low Latency10.01 Ratings00 Ratings
Data wrangling and preparation6.01 Ratings00 Ratings
Linear Scale-Out9.01 Ratings00 Ratings
Data Enrichment10.01 Ratings00 Ratings
Best Alternatives
Apache FlinkOracle Stream Analytics
Small Businesses
IBM Streams
IBM Streams
Score 9.0 out of 10
IBM Streams
IBM Streams
Score 9.0 out of 10
Medium-sized Companies
Confluent
Confluent
Score 7.4 out of 10
Confluent
Confluent
Score 7.4 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 7.9 out of 10
Spotfire Streaming
Spotfire Streaming
Score 7.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache FlinkOracle Stream Analytics
Likelihood to Recommend
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache FlinkOracle Stream Analytics
Likelihood to Recommend
Apache
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.
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Oracle
No answers on this topic
Pros
Apache
  • 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
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Oracle
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Cons
Apache
  • 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
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Oracle
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Alternatives Considered
Apache
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.
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Oracle
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Return on Investment
Apache
  • 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
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Oracle
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ScreenShots