Smarter Data Management with Oracle:
AI and Automation in Modern
Database Technologies

Smarter Data Management with Oracle: AI and Automation in Modern Database Technologies

Data has become the most valuable asset in the enterprise, but traditional approaches to database management often struggle to keep up with modern demands. Oracle has redefined the role of the database by embedding artificial intelligence and automation across its data platform. These innovations not only improve performance and reduce operational effort, they also position the Oracle Database as a foundational enabler for AI-driven applications and intelligent automation.

From self-managing capabilities in Autonomous Database to support for vector search and natural language queries in Oracle Database 23c, Oracle is pushing the boundaries of what a modern enterprise database can do. This blog highlights the key advancements in Oracle’s database portfolio and how organizations can benefit from smarter, AI-powered data infrastructure.

Autonomous Database: Self-Driving, Self-Securing, and Self-Repairing

Oracle Autonomous Database eliminates much of the manual work associated with database administration. It uses embedded machine learning to automate key operations such as:

Indexing, tuning, and query optimization
Security patching and configuration
Backup, recovery, and fault resolution

The database continuously monitors performance and makes adjustments in real time, without human intervention. It can detect patterns in workload behavior and adjust memory, parallelism, or execution plans to optimize performance automatically.

Benefits include:

Lower administrative overhead
Improved uptime and security posture
More consistent performance across diverse workloads

For many organizations, Autonomous Database provides a way to modernize without adding complexity or hiring additional database specialists.

Oracle Database 23c: Built for AI, Search, and Application Development

Oracle’s latest flagship release, Oracle Database 23c, introduces capabilities designed to support modern application and AI use cases.

AI Vector Search

Oracle 23c can store and index vector embeddings (numerical representations of unstructured data like text or images) and perform semantic similarity searches. This allows developers to:

Run similarity queries across documents, images, or audio
Build applications that combine private enterprise data with large language models (LLMs)
Support retrieval-augmented generation (RAG) use cases without moving data to a separate vector store

By embedding vector search directly in the database, Oracle simplifies AI solution architecture and reduces data duplication.

Select AI and Natural Language Queries

Select AI allows users to ask natural language questions against their data. The database translates those questions into SQL, retrieves relevant data, and optionally passes results to a large language model for summarization.

Use cases include:

Enabling business users to query data without writing SQL
Embedding question-answering features into dashboards or applications
Allowing developers to build conversational interfaces that retrieve data from structured sources

Oracle integrates this feature with its own AI services as well as providers like Cohere and OpenAI.

JSON Relational Duality and Developer Productivity

Oracle Database 23c supports JSON-relational duality, allowing developers to work with data as JSON documents or as relational tables, without sacrificing performance or consistency. This supports:

Modern application development with flexible data models
Simplified integration between microservices and enterprise systems
Easier evolution of schemas in cloud-native applications

Developers can build faster with native JSON support, REST APIs, and integration with Oracle APEX and low-code tools.

In-Database Machine Learning

Oracle Machine Learning (OML) allows organizations to build, train, and deploy machine learning models directly inside the database. This eliminates the need to move data to external platforms and reduces latency and data governance risks.

Capabilities include:

Support for classification, regression, clustering, and anomaly detection
AutoML for automated model selection and tuning
Integration with Python, SQL, and REST APIs
Deployment of models as scoring functions or web services

Models can be trained on data in-place and then used to generate predictions in real time, embedded in business logic or reporting pipelines.

Business Value for Data-Driven Enterprises

Oracle’s innovations in database technology deliver clear value for enterprise teams seeking to modernize their data platforms:

Improved agility with native support for JSON, AI workloads, and hybrid data models
Faster time to insight through embedded analytics, ML, and natural language interfaces
Operational efficiency with self-managing capabilities that reduce reliance on manual DBA tasks
AI readiness with built-in support for vector search, model hosting, and integration with LLMs
Stronger governance by keeping sensitive data and ML models in a single, secure platform

These advantages help CIOs and data leaders deliver better business outcomes while lowering risk and cost.

How Vigilant Helps Clients Maximize Oracle Database Technologies

Vigilant helps clients modernize and optimize their Oracle data environments by:

Migrating on-premise databases to Autonomous Database and OCI
Enabling AI use cases through vector search and in-database ML
Designing and implementing data governance and security frameworks
Building modern applications with low-code, JSON, and RESTful interfaces
Integrating Oracle Database with analytics, cloud services, and enterprise systems

Whether you’re planning a cloud migration, embedding AI into your data stack, or optimizing Oracle licensing and architecture, we provide the technical depth and advisory experience to deliver results. Explore Vigilant’s database services or contact us to learn how Oracle’s modern database technologies can help you simplify operations, accelerate development, and prepare for the next generation of intelligent applications.