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DTSTAMP:20261103T091709Z
DTSTART:20261105T173000Z
DTEND:20261105T181500Z
SUMMARY:Fresh Data or Fast Retrieval? Lightning Tables Give Agents Both
LOCATION:Meet-Up Hub
DESCRIPTION:RJ Atwal\, Vasudha Khare\n\nData today lives in two worlds: at 
 rest\, where you can query it\, and in motion\, streaming through systems 
 like Apache Kafka®\, built for throughput and ordering\, not for querying
 . Bridging them means copying data out of the stream through connectors an
 d stream processors into a warehouse or OLAP database\, and every hop adds
  latency\, a new copy\, and one more thing that can break. This does not w
 ork for agents. Agents decide what to ask at runtime\, chain dozens of ret
 rievals per task\, and act on what they read\, so latency stacks up and st
 ale data leads to wrong actions and consequences. Now lightning queries cl
 ose that gap: a stream-native OLAP engine that queries streaming data dire
 ctly\, without ever copying it out. In this talk\, you'll walk away with a
  working model for designing a stream-native query engine\, one that holds
  fresh log records and historical columnar data in one place and answers q
 ueries consistently across both\, with no gap between what just happened a
 nd what you can query. You'll see how lightning queries serve ad-hoc filte
 rs and lookups without pre-built cubes while staying low-latency\, and the
  API design choices that made that possible. Most importantly\, you’ll l
 earn how to instantly serve fresh business context for your AI agents\, re
 al-time analytics\, and operational apps.
URL:https://sf26.rmoff.net/s/fresh-data-or-fast-retrieval-lightning-tables-
 give-agents-234
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