How ByteDance’s Volcano Engine Rebuilt Its AI Stack on Lance, From Data Lake to Agent Memory at 100K+ QPS

Volcano Engine, ByteDance's cloud and AI service platform, has significantly integrated Lance and LanceDB into its data infrastructure to enhance its AI capabilities and overcome limitations faced by traditional analytics pipelines. By adopting Lance, the platform improved its model training pipeline efficiency from seven days to one day, increased GPU utilization to 95%, and supported enterprise agent memory at over 100,000 queries per second in production. Lance's open lakehouse format provided native multimodal support and superior performance for random access, addressing the constraints of Parquet-based alternatives. This integration led to the development of ArkClaw, a managed cloud version of the OpenClaw agent framework, which utilized LanceDB as its memory backbone for scalable, multimodal, and versioned memory retrieval. The platform's innovations included distributed IVFPQ index training, binary copy compaction, and an observability tooling suite, contributing over 27 features back to the open-source community. Looking forward, Volcano Engine aims to further develop native agent-data patterns and a three-layer system called CloudLake, which unifies memory, knowledge, and training data using Lance.

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