NeurDB 0.5.0 released

We are pleased to release NeurDB v0.5.0, bringing substantial enhancements in AI-powered data analytics and autonomous operations.

In this version, we released the following key features:

In-Database Model Management

• Integrated a database-native deep learning model store (NeurStore) for efficient model persistence and retrieval.
• Optimized model loading and saving mechanisms with reduced storage overhead and improved I/O performance.
• Enhanced metadata tracking to support multi-version model management and dependency tracing.

Concurrency Control Enhancement

• Refined the NRAM (NeurDB Access Method) for improved transaction throughput under mixed workloads.
• Enhanced lock management and state abstraction for learned concurrency control (NeurCC).
• Added test cases to validate transaction isolation and detect potential anomalies.

KV-based Storage Engine Enhancement

• Integrated an inter-process communication (IPC) channel to reduce context-switch overhead and improve latency.
• Added test cases to validate correctness under concurrent read/write.

Automatic Data Preparation Pipeline

• Introduced an automated data preparation and feature transformation pipeline for AI analytical queries.
• Supports training-ready dataset generation.