Alok Giri Oracle

  Oracle 23c AI Sharding: An In-Depth Exploration . As technology continues to evolve, managing large-scale databases efficiently and securely has become a critical challenge. Oracle 23c introduces advanced capabilities in AI-driven database sharding, offering a robust solution for scaling modern applications. This comprehensive exploration delves into the various aspects of Oracle 23c AI Sharding, highlighting its features, benefits, and potential applications, particularly focusing on how these innovations can cater to your projects and interests. Introduction to Database Sharding Database sharding is a method of partitioning data across multiple databases, known as shards, which can be stored on different servers or geographic locations. This approach allows for horizontal scaling, enabling the database to handle large volumes of data and high traffic loads by distributing the workload across multiple nodes. Oracle 23c enhances traditional sharding with AI-driven features, providing

  Oracle Database 23c, also known as "Oracle 23c AI" or "23ai," introduces several significant enhancements and features, particularly focused on AI integration, advanced data management, and application development. Below is a detailed breakdown of the notable features: 1. AI Vector Search AI Vector Search is a major innovation in Oracle 23c, designed to facilitate the search of data based on conceptual content rather than specific keywords or values. This feature allows for: Semantic Search : Enables searches based on the meaning of documents, images, and structured data. It allows for more intuitive and accurate retrieval of information by understanding the context rather than relying solely on keyword matching. Large Language Models (LLMs) : Supports LLMs, which can query private business data using natural language. This is particularly useful for extracting relevant information from large datasets without requiring specialized query knowledge. Integration with