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VERSION:2.0
PRODID:-//CFP.DEV//CFP.DEV shortcodes//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:VoxxedDays CERN
X-WR-RELCALID:c426493a-54d4-472b-b975-6f3aaa7163fa
X-WR-TIMEZONE:Europe/Brussels
BEGIN:VEVENT
UID:cfp-1151-6410@cfp.dev
DTSTAMP:20260920T150218Z
SEQUENCE:0
STATUS:CONFIRMED
DTSTART:20250115T094500Z
DTEND:20250115T103000Z
SUMMARY:One Does Not Simply Query a Stream
DESCRIPTION:Suppose you have embraced Apache Kafka as the core of your data
  infrastructure. In that case\, you have probably integrated event-driven 
 services to communicate with each other through topics\, combined with leg
 acy systems through an ecosystem of connectors\, and responded more or les
 s in real-time to things happening in the world outside your software. Imm
 utable logs of events form a more robust backbone than the one-database-to
 -rule-them-all of your profound monolith past. Your stack is more evolvabl
 e\, responsive\, and easier to work with. However\, you might face a chall
 enge now that everything is a stream - how do you query things? Although y
 ou may name at least one or two ways off the top of your head\, it&#39\;s 
 time you think through how to make the choice. In this talk\, we&#39\;ll e
 xplore the solutions currently in use for asking questions about the conte
 nts of a topic\, including Kafka Streams\, the various streaming SQL imple
 mentations\, your favorite relational database\, your favorite data lake\,
  and real-time analytics databases like Apache Pinot or Clickhouse. There 
 is no single correct answer to the question\, so as responsible builders o
 f systems\, we must understand our options and the trade-offs they present
  to us. You&#39\;ll leave this talk even more satisfied that you&#39\;ve e
 mbraced Kafka as the heart of your system and are ready to deploy the righ
 t choice for querying the logs that hold your data.\nSpeakers: Viktor Gamo
 v\nTrack: Data & AI
URL:https://vdc25.voxxeddays.ch/talk/one-does-not-simply-query-a-stream/
LOCATION:Globe\nCERN\nGeneva\, Switzerland
CATEGORIES:Data & AI
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