Agent swarms will certainly break the data infrastructure we have built for humans. Agents always n...
elvis(@omarsar0) · 人工智能
Agent swarms will certainly break the data infrastructure we have built for humans. Agents always need the latest records and the full history to complete tasks correctly. Take a look at what @Eon_io_ is building: a new data infrastructure to keep data fresh as it arrives in open Iceberg tables in your own bucket. Agents get context on each table over MCP. In Eon's public benchmark, it used 4x less compute than Spark and 7x less than Flink. Ofir Ehrlich @OfirEhrlich What I'm seeing across the industry right now is that the biggest bottleneck to AI adoption isn't model capabilities. It's data infrastructure. Today, we're expanding the Eon Data Foundation with the launch of Eon Yukon, a new serverless data engine purposely built to change that. AI agents need fresh, contextualized data to act. Specialized models need a continuous feed of data and feedback to improve. Both are still served by a stack, an architecture, and methods built for dashboards: -Spark and Flink clusters sized for peak, plus compaction jobs to keep tables usable. -A pipeline and a copy for every consumer, staged bronze to silver to gold. -Hand-written jobs, wired together by an orchestrator and kept alive by specialists. The result: shipping data is complicated, risky, and expensive. While coding agents ship apps in hours, they rarely build or run data pipelines. The data is too volatile, and a mistake costs too much. With Yukon, data moves from ingestion to processing to serving in one continuous flow, without the infrastructure and pipelines traditionally required to connect them. Events become compacted, sorted, deduplicated Iceberg tables within seconds. Real-time aggregations run inline, with fully managed state. Agents and applications can access fresh data with sub-millisecond latency through a Redis-compatible API or through our SQL and spark compatible query engine. Beyond moving and serving data, Yukon makes it continuously understandable - Live column-level statistics, accessible throu