Channel
@kafkastreamingit
On this record: Growth · Engagement · Posts · Polls · Citations · Cite this entry
98subscribers
-1 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001403063363 |
|---|---|
| Type | Channel |
| Username | @kafkastreamingit |
| Created | Between 1 April 2019 and 21 September 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 August 2026 |
| Last confirmed live | 30 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 30 August 2026 |
| On Telegram | t.me/kafkastreamingit |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 30 Aug 2026, 20:28 | 98 | -1 |
| 9 Aug 2026, 11:16 | 99 | no change |
| 7 Aug 2026, 21:34 | 99 | first reading |
20 posts held, back to 21 September 2021 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 25 January 2022. An engagement rate over an empty window would be a number about nothing.
Apache Kafka 3.1.0 ✨è qui! Novità / lista dei KIP: Kafka broker, Producer, Consumer and AdminClient - KIP-516: Topic identifiers - KIP-773: Differentiate consistently metric latency measured in millis and nanos - KIP-768: Extend SASL/OAUTHBEARER with support for OIDC - KIP-748: Add broker count metrics Kafka Streams - KAFKA-13439: The eager rebalance protocol is deprecated - KIP-783: Add TaskId field to StreamsExc…
ksqlDB 0.22.0 🚀 è qui! Novità - Esecuzione istantanea di query con SOURCE table; - Ottimizzazione per "range-scan expressions"; - Miglioramento di push query e molto ancora. Vedi: https://twitter.com/ksqldb/status/1461397845441802246?s=21. Data Streaming IT in English: @DataStreamingIT #ApacheKafka #Kafka #ksqlDB #databases #streamprocessing #datastreamingit Invita colleghi e amici a unirsi @DataStreamingIT e @k…
🧙♂️ Apache Druid 📅 Druid Summit 2021 📆 le registrazioni video sono ora disponibili 📺: https://druidsummit.org/past-event-recordings. Data Streaming IT in in English: @DataStreamingIT #ApacheDruid #Druid #ProjectShapeshift #realtimeanalytics #streaminganalytics #ApacheKafka #Kafka #DataMesh #databases #datastreamingit Invita colleghi e amici a unirsi @DataStreamingIT e @kafkastreamingit ❤️
ksqlDB 🚀 Nuova serie di blog per lo studio dei sistemi di streaming DB 🖋 Apache Kafka PMC ed esperti 📝 Streaming Database Systems - Confluent Developer: https://developer.confluent.io/learn/streaming-database-systems. Data Streaming IT in English: @DataStreamingIT #ApacheKafka #Kafka #ksqlDB #SQL #databases #DistributedSystems #streamprocessing #datastreamingit Invita colleghi e amici a unirsi @DataStreamingIT e…
📅 10 NOV alle 10:00 CET 📆 RabbitMQ 3.9.0 🐰 dallo Stream al Cloud Native 🎙 Gabriele Santomaggio, co-autore di 📚RabbitMQ Cookbook📖, co-inventore of docs.k3ai.in Webminar gratuito: https://tanzu.vmware.com/content/webinars/nov-10-rabbitmq-3-9-0-dallo-stream-al-cloud-native. Per scoprire di più su RabbitMQ Streams + Kubernetes, guarda anche 🐇 RabbitMQ on Kubernetes Deep Dive ☸️ KubeCon + CloudNatveCon North America 2…
Apache Druid 🧙♂️ Druid Summit 2021 📅 09-10 NOV 📆 Discorsi di apertura: - Building Modern Analytics Applications with Apache Druid - Fireside Chat with the Creators of Druid - Druid Roadmap / Unveiling What's Next for Apache Druid and Imply Guest Keynote - Evolution to Data Mesh 🎙 Jay Kreps, co-creatore di Apache Kafka, Confluent CEO, autore di 📚I 💜 Logs: Event Data, Stream Processing, and Data Integration📖 Regi…
🐿 Apache Flink 📅 Flink Forward Global 2021 📅 le registrazioni video sono ora disponibili 📺: https://www.youtube.com/playlist?list=PLDX4T_cnKjD0J2LFr7yBk2aSS_o2l-7ue. Leggi anche 📝 Sort-Based Blocking Shuffle Implementation in Flink ⁃ Part One 📕: https://flink.apache.org/2021/10/26/sort-shuffle-part1.html; ⁃ Part Two 📗: https://flink.apache.org/2021/10/26/sort-shuffle-part2. Data Streaming IT in English: @DataS…
Apache Kafka ✨ Nuova Guida al Stream Processing Kafka Streams Fundamentals - Confluent Blog: https://www.confluent.io/blog/how-kafka-streams-works-guide-to-stream-processing 🖋 Bill Bejeck, Apache Kafka Committer, autore di 📚Kafka Streams in Action📖 e di 📚Event Streaming with Kafka Streams and ksqlDB📖 (MEAP) Data Streaming IT in English: @DataStreamingIT #ApacheKafka #Kafka #KafkaStreams #KStreams #streamproces…
💯 Data Streaming IT @kafkastreamingit iscritti! 🎉 Grazie di ❤️ per il sostegno 🙏🏻 Se vuoi, lascia un feedback su cosa vorresti ulteriormente leggere o approfondire sul canale (scelta multipla) 💡:
The shares total 158%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Apache Flink 🐿 Flink Forward Global 2021 📅 26-27 OTT 📆 si svolge questa settimana! Registrazione gratuita: https://www.flink-forward.org/global-2021. Data Streaming IT in English: @DataStreamingIT #ApacheFlink #Flink #FlinkForward #PyFlink #SQL #streamprocessing #datastreamingit Invita colleghi e amici a unirsi @DataStreamingIT e @kafkastreamingit ❤️
Apache Kafka ✨ Scala Nuovo "end-to-end tutorial" su Kafka Streams in Scala Kafka Streams 101 di Riccardo Cardin - Rock the JVM Blog: https://blog.rockthejvm.com/kafka-streams. Data Streaming IT in English: @DataStreamingIT #ApacheKafka #Kafka #KStreams #Scala #streamprocessing #datastreamingit Invita colleghi e amici a unirsi @DataStreamingIT e @kafkastreamingit ❤️
Apache Kafka ✨ uGroup, Nuovo servizio di Kafka consumer monitoring @ Uber 📝 Introducing uGroup: Uber’s Consumer Management Framework - Uber Engineering: https://eng.uber.com/introducing-ugroup-ubers-consumer-management-framework. Considerazioni interessanti su Apache Kafka 3.0.0, KRaft e ZooKeeper 📝 Apache Kafka 3.0 is out! But... by Jason Bell - Digitalis Blog: https://digitalis.io/blog/kafka/apache-kafka-3-0-is…
Showing the 12 most recent of 20 posts we hold for @kafkastreamingit. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
💯 Data Streaming IT @kafkastreamingit iscritti! 🎉 Grazie di ❤️ per il sostegno 🙏🏻 Se vuoi, lascia un feedback su cosa vorresti ulteriormente leggere o approfondire sul canale (scelta multipla) 💡:
The shares total 158%, above 100: this poll accepts more than one answer per voter. No per-option vote count is published, so the number of voters who chose each option is not derivable and is not shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 20 most recent posts we hold, published 21 September 2021 to 25 January 2022. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 30 August 2026 — this entry's latest reading, not the date you are reading this.
“Data Streaming IT” (@kafkastreamingit), 98 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/kafkastreamingit.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.