October 30, 2025 — 1.3 Lakehouse Platform Product Update Release Notes

This release (Release 2025.12.30) introduces a series of new features, enhancements, and bug fixes. These updates will be rolled out gradually to the following regions, expected to complete within one to two weeks from the release date. The exact timing depends on your region.

Domestic Regions

Alibaba Cloud (Shanghai)
Tencent Cloud (Shanghai/Beijing/Guangzhou)
AWS (Beijing)

International Regions

Alibaba Cloud (Singapore)
AWS (Singapore)

AI Foundation Capabilities

GenAI Function Support: Provides AI capabilities such as text generation, vectorization, document parsing, and text chunking through SQL functions. Singdata Lakehouse adopts a unified strategy of encapsulating multi-cloud vendor GenAI services, offering users a more flexible and comprehensive GenAI capability integration solution.
Semantic View Support: Added Semantic View, supporting manual/AI-automated semantic layer generation, and supporting vector and inverted indexing on key elements within a Semantic View.

New Features

Managed Iceberg Table

External Engine Support: Engine supports Iceberg split and commit.
REST Catalog: Lakehouse implements a REST Catalog service supporting external engine read/write, and supports Iceberg split and commit.

Inverted Index Feature Optimization

DYNAMIC Table Inverted Index Support: Table creation statements now support setting inverted indexes within Dynamic Tables.

Unstructured Data Processing

Stream on Volume: Supports building incremental unstructured data pipelines based on Volumes.
Volume Feature Adaptation: Internal managed Volumes now support directory tables, with white-screen development available through Studio.
Volume Metadata Sync: Added a VOLUME metadata sync switch, supporting enabling/disabling directory tables.
Volume Query Optimization: When querying a Volume without specifying a schema, schema merge is now supported.

Job Management

Job Profile: Supports viewing associated sub-tasks, improving observability and helping users understand job execution logic.

SQL Feature Enhancements

SQL Commands

Observability Improvement: show create table now supports viewing the SQL for a specific version of a dynamic table.
Copy Command Optimization: Added new Copy Into Location command parameter control to constrain the maximum export file size.
Desc Extended Output Information: desc job now supports retrieving details such as row counts, output/input file sizes.
Show Partitions Enhancement: show partitions now supports descending order.
SQL Partial Update: Supports concurrent updates to different columns of a wide table, resolving update conflict issues.

Functions

read_kafka: Supports expression-filled parameters to meet the need for previewing recent data in operational scenarios.

Ecosystem Capability Building

Databricks External Table Read Performance Optimization: Optimized Databricks Delta Lake external table read performance, improving BI analysis efficiency.
Iceberg Ecosystem Enhancement: Integrated Iceberg REST Catalog, completing Iceberg external table DML operation capabilities; supports Iceberg REST Catalog OAuth authentication.

Performance Improvements

Dynamic Table Performance Optimization: Supports SQL change detection (avoiding unnecessary full refreshes) and automatic query parameter iteration.
Data Cache Enhancement: Supports independent cache lifecycle management bound to VCs, resolving cache space shortage issues.

Developer Experience

Dynamic Table Development Experience Optimization: In large-scale data change scenarios, adaptive backfill plan generation with parameter configuration.
Job Query Data Volume Optimization: Optimized job query data volume limit from 10,000 records at the workspace level to 10,000 records at the VC level.