EventFlux – engine xử lý luồng dữ liệu nhẹ, viết bằng Rust. Chỉ cần một binary, tiêu tốn 50‑100 MB, khởi động trong mili giây, hỗ trợ >1M sự kiện/giây. Không cần Kubernetes, JVM hay Kafka; viết SQL và chạy ngay. Thích hợp cho các kịch bản streaming đơn giản, không thay thế Flink ở quy mô lớn. #EventFlux #Rust #StreamProcessing #OpenSource #XửLýDòngDữLiệu #MãNguồnMở
https://www.reddit.com/r/opensource/comments/1q739m1/eventflux_open_source_lightweight_stream/
IBM to Acquire Confluent to Create Smart Data Platform for Enterprise Generative AI
ARMONK, NY and MOUNTAIN VIEW, CA, Dec. 8, 2025 /PRNewswire/ — IBM (NYSE: IBM) and Confluent, Inc. (NASDAQ:CFLT),…
#NewsBeep #News #Topstories #acquisition #AI #ApacheKafka #ArvindKrishna #Confluent #ConfluentIntelligence #Connectors #DataStreaming #generativeAI #Headlines #ibm #JayKreps #StreamGovernance #StreamProcessing #StreamingAgents #Tableflow #TopStories
https://www.newsbeep.com/296866/
Context, not compute, is the bottleneck for AI agents.
Adi Polak @Confluent shows how stream-native context engineering with Kafka & Flink builds memory layers that scale at QCon AI New York 2025.
🔗 Explore the session: https://bit.ly/3JtFzLI
Join us in #Lucerne on October 15, 2025 for an exciting talk by Viktor Gamov about #StreamProcessing with #Apache #Flink!
Stream processing has come a long way. Today’s systems handle strict correctness guarantees, low latency, and terabytes of state. In this talk, Viktor will introduce #ApacheFlink, explain concepts like stateful and event-time stream processing, and explore its APIs and ecosystem.
More info & registration: https://www.jug.ch/html/events/2025/stateful_stream_processing.html
Stream Processing has evolved quickly in a short time: only a few years ago, stream processing was mostly simple real-time aggregations with limited throughput and consistency. Today, many stream processing applications have sophisticated business logic, strict correctness guarantees, high performance, low latency, and maintain terabytes of state without databases. Stream processing frameworks also abstract a lot of the low-level details away, such as routing the data streams, taking care of concurrent executions, and handling various failure scenarios while ensuring correctness.
⚡ Process streaming data with #PyFlink + #FlinkSQL.
See how to build pipelines using PyFlink Table API, #UDFs & #SQL—no JVM needed. Watch Diptiman Raichaudhuri demo windowing, event time processing & real-time #Kafka stream ingestion.
🎥 Click here: https://youtu.be/PnpHp3Y12xw
#StreamProcessing #FOSSASIA #OpenSource
Just kicked off Module 6 of the #DataEngineering Zoomcamp by @DataTalksClub! 🎉 It's all about #StreamProcessing with #Kafka, #Flink, and #PyFlink. Can't wait to get hands-on with real-time data streaming! 🖥️🚀
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