Tagged articles

Lance format

3 articles · Page 1 of 1

Sep 24, 2026 · Artificial Intelligence

PB-Scale Embodied Data: Efficient Storage & Training with Volcano Engine Multimodal Data Lake

Digua Robot leverages Volcano Engine's multimodal data lake — combining TOS object storage, Lance columnar format, and Ray distributed processing — to unify heterogeneous robot episode data, enable PB-scale ingestion, spatial quality checks via LAS operators, and achieve near-PFS training throughput with RobotLanceDataset.

Lance formatPB-scale dataRay distributed processing

0 likes · 22 min read

PB-Scale Embodied Data: Efficient Storage & Training with Volcano Engine Multimodal Data Lake

DataFunSummit

Apr 25, 2026 · Big Data

AI‑Era Multimodal Data Lake Infrastructure: TBDS Design, Storage, Compute, and Governance

The article analyzes how Tencent Cloud's TBDS platform tackles the AI era's multimodal data lake challenges through a native storage format (Lance), elastic Ray‑based compute, standardized metadata with Gravitino, and automated governance via Lakekeeper, citing architecture details, performance numbers, and real‑world deployments.

AI infrastructureBig DataGravitino

0 likes · 13 min read

AI‑Era Multimodal Data Lake Infrastructure: TBDS Design, Storage, Compute, and Governance

ByteDance Data Platform

Oct 29, 2025 · Big Data

How Volcano Engine’s Multimodal Data Lake Tackles AI Agent Challenges

The article explores how Volcano Engine’s multimodal data lake architecture addresses the storage, compute, and management challenges of AI agents by introducing new formats like Lance, upgrading engines such as Spark and Daft, and providing unified tools for processing, versioning, and querying massive multimodal datasets.

Big DataCloud ComputingDaft engine

0 likes · 13 min read

How Volcano Engine’s Multimodal Data Lake Tackles AI Agent Challenges