Oracle Database & Technology Trends: What’s Shaping 2026 and Beyond

The Oracle world is changing faster than ever. Companies are now using more AI, running systems across multiple clouds, and relying on instant access to data. To keep up, Oracle has introduced powerful new updates to its databases. With the launch of Oracle AI Database 26ai and major improvements in autonomous database technology, 2026 has become an important year for database professionals, architects, and tech leaders.

This blog highlights the latest Oracle database and technology trends using the most recent insights from 2025–2026.

Oracle AI Database 26ai: The New Flagship Standard

Oracle has moved from Oracle Database 23ai to the new Oracle AI Database 26ai, which focuses heavily on built‑in AI features like vector search, AI‑driven automation, and faster processing using GPUs. This new version is built on top of 23ai without changing the main database structure, so companies can upgrade more easily.

What’s improved?

• AI is now built into all types of data and workloads.
• Upgrades are easier because the base architecture remains the same.
• It works across all major clouds—OCI, Azure, Google Cloud, AWS—and on Exadata systems in data centers.

Oracle is also working closely with NVIDIA to speed up vector indexing and improve AI agent capabilities.

Oracle Database 23ai & 24c Adoption Accelerates

According to 2026 trend reports, many companies are moving away from the older Oracle 19c and upgrading to Oracle 23ai and 24c. The main reasons for this shift are:

• New AI features like Vector Search and support for large language models
• Better multitenant functionality
• Improved JSON handling and more automation

For organizations that have been postponing upgrades, 2026 is becoming the year when updating is no longer optional.

Multitenant Architecture Becomes Mandatory

By 2026, using Oracle’s multitenant architecture isn’t optional anymore—it’s required for modern database setups. This change is happening because:

• Companies are running many PDBs (pluggable databases) in one system
• More applications now use application containers
• PDB lockdown profiles are needed for better control and security
• Patching is now standardized at the CDB level

To keep up, DBAs need to learn important skills like cloning PDBs, unplugging and plugging them without downtime, and monitoring resource usage for each PDB.

AI & Automation Take Over Routine DBA Work

AI automation is no longer just a buzzword—it’s now a real part of everyday database work. Oracle’s built‑in AI features and the Autonomous Database can now handle tasks like:

• Tuning SQL automatically
• Applying patches on their own
• Detecting unusual behavior
• Optimizing workloads without manual effort

Because these routine tasks are now automated, DBAs can focus more on planning, architecture, and other strategic responsibilities.

Autonomous Database: The Self‑Driving Future

Oracle’s Autonomous Database keeps getting better with new powerful features, such as:

• Automatically increasing or decreasing compute and storage as needed
• Applying patches without any downtime
• Using built‑in machine learning to give predictions and insights
• Syncing data in real time across different global regions

The newest updates also add generative AI and AutoML directly into the database, allowing users to ask questions in natural language and get smart, automated insights.

Customer examples from 2025 and 2026 show how important the Autonomous Database has become for both transactional and analytical workloads.

Multicloud Is the New Normal

Oracle’s multicloud strategy is growing fast, with stronger integration across:

• Oracle Database@Azure
• Oracle Database@Google Cloud
• A unified AI Lakehouse using Apache Iceberg

This means customers can now run Oracle’s AI Database services on any cloud with the same performance, security, and management experience.

Overall, Oracle is making it easier for companies to use a mix of different clouds while keeping operations simple and consistent.

OCI Gains Traction in Regulated Industries

OCI (Oracle Cloud Infrastructure) is becoming more popular because:

• It offers more predictable and manageable costs
• Its architecture provides very low latency
• It meets strong security and compliance standards like FedRAMP High and IL5

Because of these benefits, government and healthcare organizations are increasingly moving their critical systems to OCI.

Security Trends: Zero‑Trust + Automated Defense

Security is now built directly into Oracle’s technology, including:

• End‑to‑end encryption to keep data safe at all stages
• Automatic security patching to fix vulnerabilities without manual work
• AI‑powered threat detection to spot risks early
• Detailed access controls to manage user permissions

Oracle is moving toward security that works quietly in the background, helping businesses stay compliant all the time without extra effort.

Patch Cycles Intensify with AI‑Optimized Releases

Oracle is releasing patches more frequently as it strengthens its AI‑powered database engine. Recent updates include:

• Important Release Updates (RUs) for 19c, 21c, and the AI Database (from 23ai to 26ai)
• Major fixes in the October 2025 patch for the optimizer, RAC, and Active Data Guard
• The 19.30 RU (January 2026) focuses heavily on security and performance

Because of these faster patch cycles, staying up to date has become critical for keeping enterprise databases stable and reliable.

Data as a Strategic Asset: Real‑Time, AI‑Ready, Unified

Oracle is moving toward a unified, AI‑ready data platform that can handle many types of data, including:

• Relational, JSON, graph, and blockchain data
• Built‑in vector stores to support RAG‑based AI
• Real‑time global analytics for instant insights

With these capabilities, Oracle is becoming a key player in enterprise‑level AI systems.

Conclusion

Oracle is changing from a traditional database company into a leader in AI‑powered infrastructure. With new technologies like Oracle AI Database 26ai, improvements in the Autonomous Database, support for multiple clouds, and built‑in generative AI, 2026 has become an important year for companies that want to modernize their data systems.

For DBAs and architects, the message is straightforward:

Move toward AI‑driven, automated, multicloud‑ready environments or risk falling behind.

Thanks for Reading !

The Future of Oracle Database Administration: Embracing New Technologies in 2025-26

 

The role of a Database Administrator (DBA) is evolving rapidly. With the surge in AI, cloud computing, and autonomous systems, Oracle Database Administration is no longer just about performance tuning or backup scripts; it's about leveraging advanced technologies to deliver smarter, faster, and more resilient data systems.

🚀 Oracle Database 23ai: The AI-Driven Engine

Oracle Database 23ai, is designed with artificial intelligence and machine learning at its core. 

The DBA now plays a strategic role in deploying AI-powered data solutions. Understanding vector indexing, AI model integration, and query optimization for ML workloads is becoming essential with its  Key Features like AI Vector Search, JSON Relational Duality Views, In-Database ML etc.

☁️ Multi-cloud & Cloud-Native DBA Tools

With Oracle’s partnerships with Microsoft Azure, Amazon AWS, and Google Cloud, hybrid and multi-cloud database deployments are now a standard enterprise architecture. DBAs are expected to be fluent in cloud architectures, familiar with DevOps practices, and comfortable managing databases in distributed, containerized environments.

Below are few important / key trends that DBAs should focus fully.

🔹 Key Trends:

• Oracle Database@Azure and OCI Interconnect streamline hybrid deployments.
• Oracle Cloud Infrastructure (OCI) offers Autonomous Database instances with serverless capabilities.

GoldenGate Microservices Architecture for real-time replication across clouds.

🧠 Autonomous Database Administration

The Autonomous Database is no longer a theoretical concept;  it's in production in thousands of organizations globally. The shift is from operational tasks to strategic oversight. DBAs must focus on data governance, security policies, user access models, and cost optimization in automated environments.  It covers below few highlights,

🔹 Automation Highlights:

• Self-patching and self-tuning
• Auto-scaling resources
• Intelligent workload optimization

🔐 Next-Gen Database Security

With growing data privacy regulations, Oracle has introduced advanced security features in its latest releases. Like Data Safe, Always Free ATP/ADW with security Zones, Blockchain, cryptography etc. DBAs must now be cybersecurity-aware. Proficiency in data masking, auditing, and encryption is crucial, as is compliance with standards like GDPR and HIPAA.

🧩 Developer-Friendly Innovations

    

Oracle is also focusing on bridging the gap between developers and DBAs, by providing new features like REST APIs and Oracle REST Data Services (ORDS), GraphQL and JSON enhancements, Integration with Visual Builder and APEX

DBAs are becoming platform enablers they are working alongside developers to deploy faster, API-driven database solutions that scale with modern application frameworks.

The future of Oracle Database Administration is not about survival, but transformation. DBAs who embrace cloud-native tools, understand AI-driven workloads, and shift toward a more strategic role in data governance and architecture will find themselves more valuable than ever. If you’re still focused only on scripts and indexes, it’s time to upskill. Oracle’s technology stack is growing smarter — and so should we

Thanks for reading !

Backup and Recovery of CDB and PDB in Oracle 19c Multitenant Architecture.

Img-01

Oracle introduced the Multitenant Architecture in Oracle 12c, and it became even better in Oracle 19c. This architecture makes it easier to manage many databases by allowing multiple Pluggable Databases (PDBs) to run inside one main Container Database (CDB) Shown in above Image (Img-01) . It helps DBAs simplify tasks like administration, patching, backup, and recovery.

For DBAs working in a multitenant setup, one of the key things to understand is how to properly back up and recover both the CDB and individual PDBs. Oracle 19c gives us strong and flexible tools; especially RMAN to protect our data and reduce downtime.

This blog gives a simple, practical explanation of how to handle backup and recovery in a multitenant environment.

1. Understanding CDB and PDB Backup Architecture

Before diving into procedures, it’s crucial to understand how backups behave in a multitenant database:

A backup taken at the CDB level covers everything inside the database environment. It includes the root container (CDB$ROOT), all pluggable databases whether they are open or closed, and also the control files and redo logs of the CDB. This type of backup is best when you want full protection for the entire database setup.

A PDB-level backup is different because Oracle 19c allows you to back up each pluggable database separately. When you back up a PDB, it only includes that particular PDB and its own datafiles. It does not include anything that belongs to the CDB, such as control files or the root container. This kind of backup is helpful when tenants maintain their own backups or when only one PDB needs to be restored to an earlier point in time. Refer below Image (Img-02) for more details.

Img-02

2. Backup of the Container Database (CDB)

2.1 Full CDB Backup

A full CDB backup makes sure that the entire database i.e. both the root and all PDB’s can be restored if needed.

RMAN Full Backup Example:

rman target /

RMAN> BACKUP DATABASE PLUS ARCHIVELOG;

OR

RMAN> RUN {

BACKUP AS COMPRESSED BACKUPSET DATABASE;
BACKUP CURRENT CONTROLFILE;
BACKUP SPFILE;
BACKUP ARCHIVELOG ALL;
}

This command backs up:

• All containers (CDB$ROOT)
• All PDBs
• Control file
• SPFILE
• Archive logs

2.2 CDB Control File Backup

BACKUP CURRENT CONTROLFILE;

2.3 CDB SPFILE Backup

BACKUP SPFILE;

2.4 Tablespace Level Backup in CDB

BACKUP TABLESPACE users;

Tablespaces in root or individual PDBs can be backed up at the CDB level, but PDB-level granularity applies.  RMAN backs up datafiles regardless of whether the PDB is open or closed, as long as the CDB instance is available.

3. Backup of a Pluggable Database (PDB)

Oracle 19c lets you back up a PDB by itself, which is very helpful when many customers or tenants share the same database i.e. in multi-tenant hosting environments.

3.1 Connect to the PDB

sqlplus / as sysdba

ALTER SESSION SET CONTAINER=pdb1;

3.2 Backup the PDB

rman target /

RMAN> BACKUP PLUGGABLE DATABASE pdb1;

3.3 PDB with Archive Logs

RMAN> BACKUP PLUGGABLE DATABASE pdb1 PLUS ARCHIVELOG;

4. Recovery of CDB and PDB

Recovery is the part where the multitenant architecture really proves how flexible it is.

4.1 Recovering the Entire CDB

If the CDB suffers corruption or major failure

Mount the CDB

sqlplus / as sysdba

STARTUP MOUNT;

RMAN Restore and Recover

rman target /

RMAN> RESTORE DATABASE;

RMAN> RECOVER DATABASE;

Open the Database

ALTER DATABASE OPEN;

4.2 Recovering a Specific PDB

Recovering a pluggable database helps make sure that any problem is limited to just that one tenant’s database and doesn’t affect others. Meaning Pluggable database recovery allows isolation of failure to only that tenant.

4.2.1 Close the PDB

ALTER PLUGGABLE DATABASE pdb1 CLOSE IMMEDIATE;

4.2.2 Startup the PDB in Mount Mode

ALTER PLUGGABLE DATABASE pdb1 MOUNT;

4.2.3 Restore and Recover the PDB

rman target /

RMAN> RESTORE PLUGGABLE DATABASE pdb1;

RMAN> RECOVER PLUGGABLE DATABASE pdb1;

4.2.4 Open the PDB

ALTER PLUGGABLE DATABASE pdb1 OPEN;

5. Point-in-Time Recovery (PITR)

5.1 CDB-Level PITR

This restores entire CDB to a previous point.

5.2 PDB-Level PITR

Most powerful multitenant feature: recover only one PDB without affecting others.

Example

RMAN> RECOVER PLUGGABLE DATABASE pdb1 

UNTIL TIME "TO_DATE('2025-05-23 10:00:00','YYYY-MM-DD HH24:MI:SS')";

Oracle creates an auxiliary instance internally for PDB PITR.

6. Best Practices for Multitenant Backup and Recovery

✔ Enable ARCHIVELOG mode
✔ Perform frequent CDB-level backups
✔ Allow tenants to manage PDB backups independently if required
✔ Store backups in separate FRA locations for large environments
✔ Use BLOCK CHANGE TRACKING to speed up incremental backups

ALTER DATABASE ENABLE BLOCK CHANGE TRACKING USING FILE '/u01/bct.dbf';

✔ Test restore and recovery regularly
✔ Use cataloged RMAN backups for enterprise environments

Conclusion

Oracle 19c’s Multitenant Architecture gives DBAs strong and flexible tools to back up and recover the entire Container Database as well as individual Pluggable Databases. Backups taken at the CDB level protect the whole system, while PDB-level backups and point‑in‑time recovery allow you to restore just one PDB when needed. This helps reduce downtime and keeps issues isolated.

By understanding and using the right multitenant backup strategies, organizations can improve availability, protect each tenant’s data, and maintain a reliable environment for critical applications.

Thanks for reading ! 

🚀 Oracle Vector Search: A Beginner’s Guide

As AI and machine learning become more popular, databases are also getting smarter. One new idea is vector search, which helps computers understand meaning; we can say similar to how humans do. Oracle has introduced Oracle Vector Search, a feature that lets you search and organize data in a smarter, more natural way. It helps computers find information based on meaning, not just matching exact words. This makes working with data faster, easier, and more AI‑friendly.

 

🤔 What is Vector Search?

Traditional search works by matching keywords. You type a word, and the system looks for that exact word or something similar. But this method struggles when you want the system to understand the meaning behind what you’re asking.

Vector search works differently. Instead of looking for exact words, it uses vectors; which are like smart number lists that capture the meaning and context of information.

This helps AI tools find results that are similar in idea, not just similar in text. So even if you don’t use the exact same words, the system can still understand what you mean and show the most relevant results.

🧠 Where Does Oracle Fit In?

Oracle has added vector search to its Autonomous Database and Oracle Database 23ai. This gives developers some powerful new abilities:

• They can store vector embeddings, which are just smart number-based versions of data that help AI understand meaning.
• They can search for similarities directly using SQL, without needing extra tools.
• They can mix vector search with normal filters like dates, categories, or customer IDs to get even better results.

In simple terms, this means you can now build things like AI chatbots, recommendation systems, and image search engines that all using your regular Oracle database.

🛠️ How It Works (In Simple Terms)

Embed Your Data: Use an AI model (like OpenAI, Hugging Face, etc.) to convert your text, image, or audio into a vector.

Store the Vectors: Insert these vectors into a special table in Oracle.

Search by Similarity: When a user enters a query, convert it into a vector and run a similarity search using Oracle’s SQL functions.

Oracle supports indexing methods like Approximate Nearest Neighbor (ANN) to keep searches fast even with millions of vectors.

 

✅ Why It Matters

Supercharges AI and ML apps

Enables semantic and context-aware searches

Runs directly in Oracle , you don’t need a separate search engine

 

Final Thoughts

Oracle Vector Search is a major upgrade for anyone building smart, AI‑based applications. It lets you add powerful, meaning‑based search features directly inside your Oracle database.

If you’re already using Oracle, turning on vector search can help you create much smarter and more user‑friendly apps by unlocking a whole new level of experience for your users.

 

 

 Thanks for reading !

Vector Search in Oracle 26ai - A Hands On Example - With FreeSQL Embed

Oracle FreeSQL is Oracle's free, browser based SQL playground that lets you write and run real Oracle Database SQL and PL/SQL directly in your web browser, no installation or setup required. It is basically for learning and practicing Oracle SQL on a real Oracle Database, offering instant access without requiring downloads or configuration. It allows you to write, run, and share SQL scripts directly online.

You can access it with below links,

https://www.oracle.com/database/technologies/oracle-free-sql/

or directly at the playground at 

https://FreeSQL.com

Oracle 26ai brings first class support for AI Vector Datatypes, letting you store embeddings and run similarity search directly inside SQL. 

In this tutorial, we will see,

1. Create a simple table with text along with vector embeddings 

2. Insert sample documents 

3. Run vector similarity search using VECTOR_DISTANCE 

4. Show how readers can experiment using a live FreeSQL worksheet

1. Create Table for Text with Vector Embeddings

 CREATE TABLE documents ( id NUMBER GENERATED BY DEFAULT AS IDENTITY   PRIMARY KEY, 

 title VARCHAR2(100), 

 content VARCHAR2(4000), 

 embedding VECTOR(3) ); 

2. Insert Sample Text along with Embeddings ,

 For simplicity, we'll manually insert tiny vectors 

INSERT INTO documents (title, content, embedding) 

VALUES ( 'SQL Tutorial','Learn the basics of SQL queries, joins, and filtering.', VECTOR('[0.12, 0.33, 0.14]')), 

('PL/SQL Stored Procedures','How to build and execute stored procedures in Oracle.', VECTOR('[0.10, 0.30, 0.11]')), 

('Machine Learning with Python','A guide to data science, python, and ML models.', VECTOR('[0.89, 0.76, 0.81]')), 

('Machine Learning with R','A guide to data science With R .', VECTOR('[0.88, 0.72, 0.80]')), 

('Machine Learning with JAVA','Data science with JAVA.', VECTOR('[0.78, 0.66, 0.58]')), 

('Machine Learning with MATLAB','Engineering Data science with MATLAB.', VECTOR('[0.91, 0.44, 0.35]')) ; 

commit;

3. Perform Vector Similarity Search 

 Suppose the user query embedding is:

SELECT 

title, 

VECTOR_DISTANCE(embedding,VECTOR('[0.11, 0.31, 0.12]'), COSINE ) AS similarity_score 

FROM documents ORDER BY similarity_score ASC 

FETCH FIRST 3 ROWS WITH TIES; 

You can use the Live FreeSQL Playground below to easily try out and understand how FreeSQL works,

Click on "Open in FreeSQL" button in below "live FreeSQL worksheet"

Login with your Oracle SSO account.

Just copy paste the above code and see the results !

 

That's it !

Hope you like it !

Thanks for reading !