At Netflix, scale drives everything.
Their logging system ingests 5 PB/day, averaging 10M+ events/sec across 40K+ microservices to serve 300M+ subscribers.
See how they did it with some key optimizations in fingerprinting, serialization, and queries.
Real-time analytics just got easier. The fully managed @ClickHouseDB sink connector is now generally available on Confluent Cloud. It’s now simpler than ever to stream data from Apache Kafka® directly into ClickHouse.
Read how it works -> https://t.co/VeUtmV4DGc
@ClickHouseDB CTO of @ClickHouseDB Alexey Milovidov, shows a mind blowing demo of air traffic telemetry indexed in ClickHouse. 150B+ records and immersive UI to explore it. This is only possible in ClickHouse. https://t.co/tpdvWiVLMO ✈️
New distributed systems protocol write-up!
Virtual Consensus (Delos) heavily inspired the new architecture in Confluent’s Kora engine, powering Freight Clusters. This write-up dives into Virtual Consensus in Delos paper and why it makes sense as the default log replication protocol in the era of object storage and hybrid environments.
https://t.co/PL7AHPKDrY
@AndreaLicata17 So your SQL would look like this:
SELECT
"__time",
"customer",
"basket",
ARRAY_AGG(LOOKUP("basketItem", 'eshop_sku'))
FROM "eshop_array" CROSS JOIN UNNEST("basket") AS b("basketItem")
GROUP BY 1, 2, 3
4/
Attention @Druidio & @ApacheKafka enthusiasts in the Munich area!
Our event, "Streamline Your Data w/ #Kafka & #Druid: Achieve Real-Time Insights" is Oct 22 w/ @Implydata's @Hellmar_Becker & @Reply_DE's Majid Azimi, hosted by Reply.
Register for free: https://t.co/DWmIPIjOek