AIDB

AIDB is a high-performance middleware designed to bridge the gap between large language models (LLMs) and relational databases. As we move into 2026, AIDB has established itself as the premier solution for 'AI-resident data' workflows, allowing engineers to execute complex inference tasks directly within SQL environments. Unlike traditional decoupled systems that require extensive ETL processes to move data to an AI model, AIDB optimizes query execution by pushing AI tasks down to the data layer. Its architecture includes an advanced AI Query Optimizer that handles model batching, result caching, and cost-aware execution plans. This ensures that enterprise data remains secure and latency is minimized. By 2026, it supports a hybrid deployment model, allowing for seamless switching between local open-weights models (via vLLM) and hosted frontier models like GPT-5 or Claude 4. It is particularly effective for real-time sentiment analysis, automated data cleansing, and semantic search over structured legacy databases without requiring a complete migration to vector-only stores.