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LangSmith launches SmithDB, a distributed database designed specifically for agent observability
AIMPACT News — May 14 (UTC+8), at the Interrupt! conference, LangChain announced the launch of SmithDB, a distributed database built on Rust, Apache DataFusion, and Vortex, focused on processing large-scale, complex agent tracking data (including multimodal content and long-span scenarios). Its architecture consists of object storage, a small Postgres metadata store, and stateless services, with no need to manage local disks, supporting elastic scaling and self-hosted deployment. In terms of performance, the tracking tree load P50 latency is 92ms, single-run load time is 71ms, run filtering is 82ms, full-text search is 400ms, and thread filtering is 131ms, with the core LangSmith experience speed improved by up to 12 times. Currently, SmithDB is fully serving production traffic, covering 100% of US cloud ingestion and tracking UI queries, and product integrations (running rules, batch export, and experimental features) are nearing completion. (Source: InFoQ)