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Exadata X11M: Oracle’s Next-Gen Intelligent Data Architecture

Ashish Ray speaks to Dataquest about Oracle's Exadata X11M extreme performance, scalability, and cost efficiency for AI, OLTP, and analytics workloads across on-premises, hybrid, and multi-cloud.

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In an exclusive conversation, Ashish Ray, VP, Mission-Critical Database Technologies from Oracle, sheds light on the Exadata X11M platform, its cutting-edge capabilities, and its role in transforming enterprise workloads. He discusses how Exadata X11M delivers extreme performance, cost efficiency, and scalability for AI, OLTP, and analytics workloads while ensuring seamless deployment across on-premises, hybrid, and multi-cloud environments. Ashish also shares insights on India’s digital transformation, multi-cloud strategies, and the future of emerging technologies like quantum computing, edge computing, and blockchain in database management.

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Excerpts

DQ: Before we dive into specifics, can you give us a quick overview of what Exadata X11M brings to the table?

Ashish: Exadata X11M is the next-generation intelligent data architecture. It provides extreme performance, scalability, and availability for data and workloads. The platform is engineered to meet the evolving needs of enterprises by ensuring fast, scalable, and highly available data access. This includes data-optimized hardware, advanced data intelligence software, and the flexibility to deploy the system in any environment—on-premises, hybrid cloud, or any public cloud. The vision behind Exadata is to enable businesses to handle modern workloads, such as AI and analytics, with the lowest possible cost. The architecture ensures that companies can deploy the platform in any form factor they prefer, without sacrificing performance or availability.

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The X11M’s innovative design combines powerful hardware, such as the latest AMD EPYC processors, with advanced software. The combination ensures businesses can process data faster, optimize resources, and maintain extreme scalability. Whether businesses need the system on-premises, in a hybrid environment, or on public clouds like AWS or Azure, Exadata X11M can be seamlessly deployed, offering extreme performance and flexibility.

DQ: What specific advancements does Exadata X11M bring to workloads like AI, OLTP, and analytics?

Ashish: Exadata X11M offers significant improvements across all major workloads:

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  • AI Workloads: The platform supports highly parallelized processing for vector searches, improving performance by 43-55%. Advanced algorithms enhance query processing, making AI workloads faster and more efficient.
  • OLTP Workloads: Transactional systems benefit from reduced latency (down to 14 microseconds) and faster transaction speeds (25% improvement). This is crucial for applications like e-commerce and stock trading.
  • Analytics Workloads: With technologies like smart scan and flash cache, Exadata delivers faster data reads and analytics processing. Flash reads are 2.2x faster, enabling quicker insights and decision-making.

DQ: Could you elaborate on how Exadata delivers cost efficiency while maintaining performance?

Ashish: Cost efficiency in Exadata X11M stems from its ability to perform more work with fewer resources. For example, the latest AMD EPYC processors provide immense computing power, enabling faster data processing. This means fewer servers are required to handle workloads, reducing energy consumption, data center space, and cooling needs.

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Additionally, Exadata incorporates advanced power management features. Businesses can automate the system to run at high power during peak times and shift to low-power modes during off-peak hours, ensuring optimal energy utilization. These measures not only lower operational costs but also enhance sustainability, which is a growing priority.

From Oracle's perspective, the cost efficiency extends to our public cloud deployments. By consolidating workloads onto fewer systems, we reduce the demand for infrastructure while delivering the same or even better performance. This approach benefits not only Oracle but also our cloud partners and customers by optimizing return on investment (ROI) across the board.

DQ: You mentioned Exadata X11M’s cost efficiency. How does it help Oracle and its customers achieve a Return on Investment (ROI)?

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Ashish: That's an excellent question. Exadata X11M's cost efficiency stems from its ability to consolidate workloads and optimize resources. For Oracle's public cloud deployment, for instance, fewer systems are now required to support a larger number of customers. This optimization reduces the demand for power, space, and cooling in our data centers, which directly improves our ROI.

For our customers, the cost efficiency translates into faster productivity. Tasks like generating month-end or quarterly reports, which previously took hours, can now be completed in significantly less time. This boost in efficiency has ripple effects throughout the business ecosystem. Customers save on infrastructure costs while enhancing their operational capabilities.

Additionally, this efficiency extends to our cloud partners like AWS and Google Cloud, who can now offer Oracle solutions with reduced overhead. The result is a symbiotic relationship where Oracle, its partners, and its customers all benefit from streamlined operations and higher returns.

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DQ: How does Exadata address challenges like data silos, latency, and data security in a hybrid environment?

Ashish: Data silos and latency are common challenges for enterprises that have accumulated disparate systems over time. Exadata addresses these issues by consolidating all workloads into a unified, scalable architecture. This eliminates the need for multiple systems to interact through APIs, reducing latency and simplifying operations.

The architecture also includes Remote Direct Memory Access (RDMA) technology, which allows ultra-fast data communication between servers and storage. This ensures that even latency-sensitive applications, such as financial transactions or flight reservations, perform seamlessly.

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When it comes to security, Exadata offers robust features to protect data across hybrid environments. The platform adheres to stringent security protocols, ensuring data integrity whether it's stored on-premises, in a private cloud, or in a public cloud environment. Exadata's ability to scale elastically without downtime further ensures operational continuity and data protection.

DQ: What are your observations on the Indian market's adoption of Exadata, and how does it cater to the unique needs of Indian enterprises?

Ashish: The Indian market is incredibly dynamic, with unique challenges and opportunities. The rapid digitization of the public and private sectors has led to a data explosion. Initiatives like UPI have showcased India's capability to scale digital solutions for a vast population. However, this scale also demands systems that are highly performant, scalable, and available.

Exadata is well-suited for the Indian market because it inherently supports these requirements. The platform's efficiency ensures that enterprises can handle massive workloads while keeping operational costs in check. Additionally, Exadata’s ability to support seamless IT modernization makes it ideal for enterprises transitioning to cloud environments.

For Indian businesses, the flexibility of Exadata is a game-changer. Whether they choose to operate on-premises, adopt hybrid cloud models, or move to public cloud platforms, Exadata ensures that the transition is smooth, with no disruption to operations.

DQ: Multi-cloud strategies are becoming a priority for organizations. What trends and challenges have you observed in this area?

Ashish: Multi-cloud strategies are no longer optional; they are essential for enterprises seeking flexibility and resilience. Historically, individual clouds operated in silos, with limited fluidity between them. This lack of interoperability created challenges during migrations, often causing disruptions.

Exadata changes this dynamic by offering seamless migration capabilities across clouds. Enterprises can run Oracle databases on their preferred cloud platforms—AWS, Azure, or Google Cloud—while maintaining consistent performance and security. This transparency allows businesses to choose the best solutions for their needs without being constrained by vendor lock-in.

The biggest challenge in multi-cloud environments is managing disparate systems. Exadata simplifies this by providing a unified architecture that supports interoperability, ensuring that businesses can operate efficiently across multiple cloud platforms.

DQ: Oracle partners with competitors like AWS, Microsoft Azure, and Google Cloud. How does this benefit Oracle and maintain its competitive edge?

Ashish: These partnerships are mutually beneficial, fostering collaboration and innovation at the R&D level. For example, when we work with AMD, we help improve their processors by testing them against Oracle's demanding workloads. Similarly, we optimize these processors for our environments, ensuring peak performance.

These collaborations also expand market opportunities. By offering Oracle database solutions on AWS, Azure, and Google Cloud, we enable these platforms to attract customers who rely on Oracle’s performance and reliability. For Oracle, this approach broadens our reach and ensures that our technology remains accessible across ecosystems.

The competitive edge comes from our laser-sharp focus on engineering and innovation. By consistently delivering cutting-edge solutions like Exadata X11M, we ensure that customers see Oracle as a leader in performance, scalability, and flexibility.

DQ: How do you foresee emerging technologies like quantum computing, edge computing, and blockchain impacting database management? What role will Oracle play in these fields?

Ashish: Emerging technologies like quantum computing, edge computing, and blockchain are transforming the way data is processed and managed. At Oracle, we view these workloads as part of a larger ecosystem of data management.

For example, our converged database approach supports structured and unstructured data, enabling seamless integration with blockchain, graph databases, and spatial workloads. With the rise of AI and generative AI, Exadata has been optimized to handle massive parallel processing, making it ideal for vector searches and machine learning tasks.

As these technologies evolve, Oracle will continue to innovate, ensuring that our solutions remain relevant and capable of handling the demands of modern workloads.

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