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Embrace the Future with Oracle Database 23ai
Elevate your data management with advanced performance, scalability, and AI capabilities.
Overview
Game-Changing Innovations
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AI for Data
Our AI for Data aims to:
1. Simplify adding AI functionality to data-driven applications for developers.
2. Integrate GenAI capabilities into Oracle Database, boosting productivity for data analysts, developers, and DBAs.
We achieve this by using AI to streamline data management, provide AI algorithms for insights, enable natural language queries, and store AI-generated vectors for efficient searches.
Key Features
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Augmenting a new generation of AI models
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Secure encoding of data
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Asking questions naturally
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Finding new insights in data
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Dev for Data
Oracle Database 23ai aims to simplify application development by reducing database interaction complexity. It allows developers to focus on creating elegant applications that meet customer needs, leading to faster development cycles in today's rapidly changing digital landscape.
Key Features
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JSON Relational Duality in a single app
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Simple SQL statements
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ACID-compliant transactions
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Property Graphs modeling complex relationships
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Mission Critical for Data
Oracle Database 23ai simplifies application development by reducing database interaction complexity. It allows developers to focus on creating elegant applications and speeds up development cycles in a rapidly changing digital landscape.
Key Features
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Shard better, faster, simpler
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Caching data made simple
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Making SQL execution safer
Key Features
A converged database to manage mission-critical workloads effectively with the power of AI and ML. Let’s discover the key features of Oracle Database 23ai.
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AI Vector Search:
Application development with AI vector search and the benefits of new-generation AI models to generate and store vectors. -
JSON Relational Duality:
Allows seamless integration and querying of JSON data within relational databases. -
JavaScript Stored Procedures:
Enables the use of JavaScript for writing and executing stored procedures within the database. -
JSON Schemas:
Provides schema definitions for JSON documents to ensure data integrity and validation.
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Property Graphs:
Facilitates the modeling and querying of graph data structures within the database. -
Data Use Case Domains:
Predefined data models tailored to specific industry use cases for rapid deployment. -
Schema Annotations:
Adds metadata to database schemas for better data organization and management. -
Resources:
Provides up to 2 CPUs for foreground processes, 2 GB of RAM, and 12 GB of user data on disk.
See The Team In Action
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See The Team In Action
Upcoming Events
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- All
- GenAI
What did GenAI say to Mick Jaggar?