Oracle Boosts FY26 Capex forecast by $15B to Handle AI Demand

Oracle anticipates its FY 2026 capital expenditures will be $15 billion higher than previously projected, fueled by investments to support growing AI workloads.

The increased spending is linked to a surge in the companyS Remaining Performance Obligations (RPO) – contracted services clients haven’t yet paid for.

During the fiscal Q2 2026 earnings call, Oracle Principal Financial Officer Doug Kehring stated, “Given the added RPO this quarter that can be monetized quickly starting next year, we now expect fiscal 2026 capex will be about fifteen billion higher than we forecasted after Q1.”

Oracle’s backlog grew by $68 billion in the quarter ending November 30, reaching a total of $523 billion, driven by commitments from Meta and Nvidia. This significant backlog provides a buffer against Oracle’s reliance on OpenAI,which has committed to spending $300 billion with Big Red over the next five years despite currently operating at a loss.

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Choosing the Right Database: A Comprehensive Guide

Selecting the right database is a critical decision for any application or system that needs to store and retrieve data. With a multitude of options available, from traditional relational databases to modern NoSQL solutions, making the best choice can feel overwhelming.This guide breaks down the key considerations and popular database types to help you navigate this complex landscape.

Understanding Your Data Needs

Before diving into specific database technologies, it’s essential to understand your data requirements. Consider these factors:

• Data structure: Is your data highly structured with clear relationships (like customer information), or is it more flexible and schema-less (like social media posts)?
• Data Volume: How much data do you anticipate storing now and in the future?
• Read/write Ratio: Will your application primarily read data, write data, or a mix of both?
• Scalability: How easily does the database need to handle increasing data volumes and user traffic?
• Consistency Requirements: How crucial is it that data is promptly consistent across all parts of the system?

Relational Databases (SQL)

Relational databases, frequently enough referred to as SQL databases, have been the industry standard for decades. They store data in tables with predefined schemas, enforcing relationships between data points.

Popular SQL Databases:

• MySQL: An open-source database known for its reliability and ease of use. MySQL Official Website
• PostgreSQL: Another powerful open-source option, renowned for its adherence to SQL standards and advanced features. PostgreSQL Official Website
• Microsoft SQL Server: A commercial database offering robust features and integration with the Microsoft ecosystem. Microsoft SQL Server Official Website
• Oracle Database: A highly scalable and feature-rich commercial database often used in enterprise environments. Oracle Database Official Website

When to Choose a Relational Database:

• When data consistency is paramount.
• When your data has a well-defined schema.
• When you need complex joins and transactions.
• For applications requiring ACID properties (Atomicity, consistency, Isolation, Durability).

NoSQL Databases

NoSQL databases offer a different approach to data storage, prioritizing flexibility and scalability over strict schema enforcement. They come in various types,each suited for specific use cases.

Types of NoSQL Databases:

• Document Databases: Store data in JSON-like documents. (e.g., MongoDB)
• Key-Value Stores: Store data as key-value pairs. (e.g., Redis, DynamoDB)
• Column-Family Stores: Store data in columns rather than rows. (e.g., Cassandra)
• Graph Databases: Store data as nodes and relationships, ideal for social networks and recommendation engines. (e.g., Neo4j)

Popular NoSQL Databases:

• MongoDB: A popular document database known for its flexibility and scalability. MongoDB Official Website
• Redis: An in-memory data store frequently enough used for caching and session management. Redis Official Website
• Cassandra: A highly scalable column-family store designed for handling massive amounts of data. Cassandra Official Website
• Neo4j: A leading graph database for managing complex relationships. Neo4j Official Website

When to Choose a NoSQL Database:

• When you need to handle large volumes of unstructured or semi-structured data.
• When scalability and high availability are critical.
• When your schema is likely to evolve over time.
• For applications that don’t require strict ACID properties.

Comparison Table: SQL vs. NoSQL