{"slug":"flink-vs-apache-storm","title":"Apache Flink vs Apache Storm","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","faqCount":5,"faqs":[{"question":"What's the main difference between Flink and Storm?","answer":"Apache Flink provides exactly-once semantics and event-time processing with sub-100ms latency, while Storm offers at-least-once processing and processing-time only with 500ms-2s latency. Flink is optimized for modern, large-scale stream processing, while Storm is simpler but less powerful for complex scenarios."},{"question":"Which is faster for real-time processing?","answer":"Apache Flink is significantly faster with sub-100ms end-to-end latency compared to Storm's 500ms-2s. Flink also handles 20x higher throughput (20M vs 1M events/sec), making it the clear choice for low-latency applications like fraud detection and real-time trading."},{"question":"Does Storm support event-time windows like Flink?","answer":"No. Apache Storm only supports processing-time windowing, meaning it cannot correctly handle out-of-order or late-arriving data. Flink's event-time semantics with watermarks solve this problem, making Flink essential for applications where event arrival order matters."},{"question":"Can Storm guarantee exactly-once processing?","answer":"Storm only offers at-least-once semantics, meaning events may be processed multiple times in failure scenarios, resulting in duplicate data. Apache Flink guarantees exactly-once processing semantics, ensuring each event is processed exactly one time regardless of failures."},{"question":"Is Storm still actively maintained?","answer":"Apache Storm receives maintenance updates but has significantly lower activity (80+ commits/month vs Flink's 1,200+). With 72% of enterprises now using Flink vs 12% using Storm (2024), Flink has become the industry standard for stream processing."}],"faqPageSchema":{"@context":"https://schema.org","@type":"FAQPage","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#faq","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","inLanguage":"en-US","name":"Apache Flink vs Apache Storm — FAQ","description":"Frequently asked questions about Apache Flink vs Apache Storm","dateModified":"2026-06-17T23:18:10.327Z","author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"},"publisher":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"},"isPartOf":{"@type":"Article","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#article"},"license":"https://creativecommons.org/licenses/by/4.0/","speakable":{"@type":"SpeakableSpecification","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#faq-speakable","cssSelector":[".faq-answer"]},"mainEntity":[{"@type":"Question","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#q1","name":"What's the main difference between Flink and Storm?","answerCount":1,"acceptedAnswer":{"@type":"Answer","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#a1","text":"Apache Flink provides exactly-once semantics and event-time processing with sub-100ms latency, while Storm offers at-least-once processing and processing-time only with 500ms-2s latency. Flink is optimized for modern, large-scale stream processing, while Storm is simpler but less powerful for complex scenarios.","inLanguage":"en-US","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","upvoteCount":1,"author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"}}},{"@type":"Question","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#q2","name":"Which is faster for real-time processing?","answerCount":1,"acceptedAnswer":{"@type":"Answer","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#a2","text":"Apache Flink is significantly faster with sub-100ms end-to-end latency compared to Storm's 500ms-2s. Flink also handles 20x higher throughput (20M vs 1M events/sec), making it the clear choice for low-latency applications like fraud detection and real-time trading.","inLanguage":"en-US","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","upvoteCount":1,"author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"}}},{"@type":"Question","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#q3","name":"Does Storm support event-time windows like Flink?","answerCount":1,"acceptedAnswer":{"@type":"Answer","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#a3","text":"No. Apache Storm only supports processing-time windowing, meaning it cannot correctly handle out-of-order or late-arriving data. Flink's event-time semantics with watermarks solve this problem, making Flink essential for applications where event arrival order matters.","inLanguage":"en-US","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","upvoteCount":1,"author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"}}},{"@type":"Question","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#q4","name":"Can Storm guarantee exactly-once processing?","answerCount":1,"acceptedAnswer":{"@type":"Answer","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#a4","text":"Storm only offers at-least-once semantics, meaning events may be processed multiple times in failure scenarios, resulting in duplicate data. Apache Flink guarantees exactly-once processing semantics, ensuring each event is processed exactly one time regardless of failures.","inLanguage":"en-US","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","upvoteCount":1,"author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"}}},{"@type":"Question","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#q5","name":"Is Storm still actively maintained?","answerCount":1,"acceptedAnswer":{"@type":"Answer","@id":"https://www.aversusb.net/compare/flink-vs-apache-storm#a5","text":"Apache Storm receives maintenance updates but has significantly lower activity (80+ commits/month vs Flink's 1,200+). With 72% of enterprises now using Flink vs 12% using Storm (2024), Flink has become the industry standard for stream processing.","inLanguage":"en-US","url":"https://www.aversusb.net/compare/flink-vs-apache-storm","upvoteCount":1,"author":{"@type":"Organization","@id":"https://www.aversusb.net/#organization","name":"A Versus B"}}}]}}