Oracle Database 23c important features

 

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 Existing Applications: The feature can be seamlessly integrated into current business applications, allowing companies to implement AI capabilities without overhauling their existing systems. The AI Vector Search also benefits from the performance of Oracle Exadata systems, which accelerate search operations by several orders of magnitude​ (Oracle Blogs)​​ (Oracle)​.

2. JSON Relational Duality

This feature addresses the traditional divide between relational and document-based data models:

  • Unified Data Model: Allows developers to use JSON to retrieve and store data while maintaining the relational data model's consistency and efficiency. It provides a dual approach where the same data can be accessed either as structured relational data or as JSON documents.
  • Ease of Use: Developers can use SQL and REST APIs to interact with the database, making it easier to develop applications that need to handle both structured and unstructured data seamlessly​ (Oracle Blogs)​​ (Oracle)​.

3. Property Graphs

Oracle 23c introduces robust support for property graphs, enabling the modeling and querying of complex relationships:

  • Graph Queries: Developers can execute property graph queries using the new ISO standard SQL/PGQ syntax. This makes it easier to navigate and analyze relationships, such as those in financial transactions or social networks, directly on the database.
  • Data Integration: Property graph models can be applied to various data types supported by Oracle Database, including relational, JSON, and spatial data​ (Oracle)​.

4. Oracle True Cache

True Cache is a middle-tier cache that significantly improves application performance:

  • In-Memory Caching: Provides high-performance data access with transactionally consistent, always-updated data.
  • Application Transparency: The cache operates transparently, meaning that developers do not need to write specific code to manage the data in the cache. It supports all Oracle Database query capabilities, making it a versatile tool for improving response times​ (Oracle Blogs)​​ (Oracle)​.

5. OCI Generative AI Service

Oracle 23c integrates generative AI capabilities across its stack:

  • Generative AI Models: Supports LLMs from Cohere and Meta Llama 2, which can handle tasks like text generation, summarization, and semantic similarity analysis.
  • Multilingual Capabilities: The service supports over 100 languages, enhancing its usability in global enterprises.
  • Fine-Tuning and Customization: Enterprises can fine-tune these models using their own data, making them highly adaptable to specific business needs. The service also includes a beta feature for AI Quick Actions, enabling no-code access to open-source LLMs​ (Oracle)​.

6. Enhanced Security and Data Management

Oracle 23c introduces several security and data management improvements:

  • Blockchain and Immutable Tables: These features offer tamper-proof data storage by using cryptographic methods. The system prevents unauthorized changes and supports audit trails, making it ideal for applications requiring high data integrity, such as financial ledgers and legal records.
  • Column-Level Auditing: This allows for more precise audit policies by targeting specific columns, reducing the amount of unnecessary audit data and improving security oversight.
  • Schema Privileges: Oracle 23c introduces schema-level privileges, simplifying the management of database security by allowing more granular control over who can access specific data objects​ (Oracle)​.

7. Developer-Focused Features

  • Free Developer Databases: Oracle offers free Autonomous Database instances for developers to experiment with the new features, including AI Vector Search and JSON Relational Duality. This encourages innovation and lowers the barrier to entry for using advanced database features​ (Oracle)​.

8. SQL Firewall

  • Anomaly Detection: The SQL Firewall feature helps detect and prevent unauthorized SQL activities, such as SQL injection attacks. It logs SQL queries and can block suspicious activities, providing an additional layer of security for the database​ (Oracle)​.

Oracle 23c AI's extensive feature set aims to simplify AI integration, enhance data management capabilities, and provide robust security measures, making it a powerful tool for modern enterprises looking to leverage advanced technologies in their business operations.

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