What Oracle’s 2024 Global Survey Reveals About Top Databases, Cloud, and AI

1. Highlights of the 2024 Survey

The Oracle 2024 global user survey collected extensive feedback on company size, roles, industries, favorite databases, cloud services, database capabilities, hot topics, AI assistance, and future AI expectations. The author rates Oracle’s overall score a perfect 10, emphasizing its scalability, comprehensive data management, performance optimization, security, and integration.

2. Oracle’s View of Mainstream Databases

1. Oracle Autonomous DB: cloud‑native autonomous database
2. MongoDB: distributed document store
3. PostgreSQL: leading open‑source relational DB
4. SQL Server: client/server RDBMS
5. Azure SQL Database: DBaaS on Microsoft Azure
6. MySQL: popular relational DB for web apps
7. Snowflake: cloud data‑warehouse
8. Amazon Redshift: fully managed petabyte‑scale warehouse
9. Amazon RDS: managed relational DB service
10. Amazon Aurora: MySQL/PostgreSQL‑compatible engine
11. Firebase: real‑time backend database
12. Azure Databricks: unified analytics platform
13. Redis: key‑value store

These databases also rank highly in the DB‑Engines Ranking for September 2024.

3. Key Considerations When Choosing a Database

Selecting a database involves budget, technical requirements, organizational constraints, and desired outcomes. Important factors affect performance, scalability, security, usability, and total cost of ownership.

4. Advantages of Oracle Cloud Infrastructure (OCI)

Global footprint with multiple regions and availability domains ensures business continuity and data safety.

Flexible Virtual Cloud Network (VCN) allows highly customizable networking.

Robust security lists and routing tables give precise traffic control, protecting against unauthorized access.

Service Gateway and Load Balancer improve performance and reliability under heavy traffic.

Efficient compute resources and streamlined workflows provide a powerful, flexible, and secure cloud platform.

Migration challenges include lack of Oracle migration tools, missing features for custom requirements, preference for private or hyper‑converged clouds, complex target architectures, and regulatory or security concerns about moving production data to the cloud.

1. Absence of Oracle migration tools and direct support channels
2. Missing OCI features for specific enterprise customizations
3. Preference for private or hyper‑converged clouds over OCI
4. Complex target system architecture, especially in large manufacturers
5. Security and compliance concerns about exposing core production data

5. AI Scenarios and Expectations

Enterprises are increasingly adopting AI to boost efficiency, cut costs, and improve user experience. In manufacturing, AI supports production planning, quality control, equipment maintenance, supply‑chain optimization, and data‑driven market forecasting.

Generative AI, a key AI branch, creates new content resembling training data using models such as GANs, autoencoders, and variational autoencoders. It learns data distributions to generate realistic samples, requiring large training datasets and enabling applications from design generation to automated article writing.

6. Summary

Oracle continues heavy investment in cloud services, AI, and machine‑learning platforms such as Oracle AI and Oracle Data Science Cloud, aiming to enable intelligent decision‑making and business optimization. New database innovations—including autonomous databases and blockchain databases—are expected to improve performance, reliability, and security.