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

DataFunSummit

Dec 2, 2024 · Big Data

Gravitino Powers TBDS Product Architecture Upgrade with a Unified Metadata Lake

This article explains how Tencent Cloud's TBDS platform evolves its architecture by adopting Apache Gravitino as a unified metadata lake, detailing the challenges of legacy versus new lakehouse designs, storage and compute separation, unified data access, permission management, and the resulting benefits for big‑data and AI workloads.

Big DataGravitinoLakehouse

0 likes · 15 min read

Gravitino Powers TBDS Product Architecture Upgrade with a Unified Metadata Lake