At XCI we chase what comes next. Next innovation. Next technology. Next job done. That's why our LEX and Next teams went to 𝗙𝗹𝗶𝗻𝗸 𝗙𝗼𝗿𝘄𝗮𝗿𝗱 𝟮𝟬𝟮𝟰, to dive into the latest developments in the Apache Flink framework. This was also part of XCI's “Empower Your Knowledge” plan for our development department 🚀 They returned with insights on new ways to harness the technology and got a glimpse into what’s around the corner in data streaming. And of course, they strengthened their team bond 💪 #xci #nexttechnology #empoweryourknowledge #apacheflink #datastreaming #flinkforward2024
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Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
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Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
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Talent Acquisition Leader | Strategic Business Partner | Relationship Builder | Data-Driven Strategies | Talent Mapping | Process Optimization | XFN Partner
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
-
Delete the duplicates! With exactly-once semantics, #ApacheFlink can support a large deployment of hundreds or thousands of compute notes that run continuously, even in the event of machine failure. This ensures that there is no duplicated data and no data is left unprocessed. How is this achieved? Learn more about how Flink enables exactly-once processing for your real-time streaming data. 📺 Watch it here ⬇️
Exactly-Once Processing in Apache Flink
confluent.smh.re
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🔥 HAPPENS THIS THURSDAY! 🔥 Yingjun Wu will dissect the concept of "unified streaming and batch processing" in data systems while explaining how RisingWave users can execute both streaming and batch processing within a single system. 🎫 Save your spot here: https://lnkd.in/g7Y6Vm_g #risingwave #dataprocessing #streamprocessing #batchprocessing
CEP architect hos Xci.dk
2moGreat #Flinkforward24 conference. We learned a lot and will continue to use the technology to create great products for our customers.