The News: Cloud-based data platforms are intended to help organizations get more value from their data, share information with everyone that needs it, and reduce costs. The theory is that they provide more integration and lower costs than on-premises environments where application and data silos lead to low utilization rates and high expenses. Unfortunately, across the solutions we examined, theory does not match reality with cloud-based data platforms because they typically are almost as inefficient as on-premises deployments. Why? Because they run many different services, each of which is overprovisioned to avoid scaling-driven downtime. The fact that we see that they do not work well with many business-critical applications does not help either.
From our perspective, a data platform should be a comprehensive, open, and integrated suite of services that meets the end-to-end data needs of an organization’s portfolio of applications and use cases. It should include high levels of automation that make it easy to manage and use while providing high performance and security. Accordingly, a successful data platform must deliver across three main design principles:
- Comprehensive: The data platform should provide a comprehensive set of capabilities that support any app, use case, and data type. It should comfortably handle online transaction processing (OLTP), analytics, machine learning (ML), and mixed workloads with relational, document, spatial, graph, and other types of data. Also, management should be as automated as possible to allow scarce IT resources to focus on innovation that improves enterprise business outcomes.
- Open: The data platform should be modular, enabling organizations to use its comprehensive set of capabilities as is and extend or replace core elements with services developed by other suppliers, the open source community, or their own development organization. It does not lock customers into the capabilities offered by a single vendor but rather allows them to easily add new functionality as business needs evolve.
- Integrated: The data platform should minimize the number of separate services, integration points, and data transformations required to meet an enterprise’s full portfolio of workflows. Only when it does so will a data platform be able to help reduce complexity, improve operational efficiency, lower costs, and increase access to data from across the enterprise.
The Enterprise-Wide Benefits of a Comprehensive Data Platform
Analyst Take: In our new research report, “The Enterprise-Wide Benefits of a Comprehensive Data Platform” – done in partnership with Oracle, we analyze the current data platform requirements for enterprises and how businesses can best approach culling the search for a solution that meets its needs now and in the future.
A critical component of Oracle Data Platform is the converged database capabilities of Oracle Autonomous Database, which supports multiple types of data, workloads, and development environments with built-in AI/ML in a fully automated database service. It helps organizations consolidate data from across the enterprise and share it with everyone that needs it. Autonomous Database also automates many manual management tasks such as database provisioning, tuning, and scaling—freeing scarce resources to help the enterprise move forward business objectives. Under the covers, Autonomous Database runs on Oracle Exadata systems in Oracle Cloud Infrastructure (OCI) and enables extremely efficient consumption of database resources.
Reviewing the Competitive Landscape
We observe that both Snowflake and Amazon Web Services (AWS) demonstrate the limitation of their approaches to architecting and delivering an actual complete data platform. They profess to offer customers unlimited flexibility and choice—but when it comes to deployment choice it is, “Use my service in a public cloud, and if you need anything that I don’t offer natively, you are welcome to access those services only if they run in the same public cloud and you sign up for them, but they control their prices—we don’t.”
OCI and the Complete Oracle Data Platform
We note that Oracle is the only hyperscaler cloud provider to offer a full stack solution from infrastructure to database and enterprise-grade, AI-injected SaaS applications using a common data model. When it comes to the data platform, Oracle provides these key attributes:
- Most comprehensive
- Complete integration
- Most user friendly
- Thorough security
- Robust automation
- Most available
- Broadest deployment choices
- Best price/performance and ROI
The Benefits of Using Oracle Data Platform for All Your Workloads
Oracle Data Platform’s alignment with the core design principles of comprehensiveness, openness, and integration enables it to meet the full range of customer application and data requirements. It helps organizations achieve a diverse set of benefits that include increasing application uptime, providing better customer experiences, and improving the accuracy of business forecasts.
Getting More Value and Simplifying Operations with Data with Oracle Autonomous Database
Integral to the Oracle Data Platform vision is delivering core data management capabilities using Oracle Autonomous Database, MySQL HeatWave, and Oracle Big Data Services for Hadoop-based data lakes. Given the broad usage of Oracle Database in organizations around the world, it should be no surprise that Autonomous Database will provide this core capability for many organizations.
The Benefits of Using Oracle Autonomous Database in Oracle Data Platform
We believe Autonomous Database provides the critical database capabilities that organizations need in a comprehensive data platform. Consolidating databases with Autonomous Database allows organizations to create a single source of truth that empowers data-driven decisions at all levels of the organization, enables deeper business insights, and improves operational efficiency.
Exadata Cloud Infrastructure: Optimizing the Impact of Autonomous Database
Autonomous Database runs only on Exadata systems and benefits from their unique approach to delivering scalable performance. First deployed over 13 years ago, Exadata was one of the first database platforms to separate database compute and storage resources – something that other data platform vendors have recently been touting as freshly innovative. More importantly, Exadata was the first to distribute database functionality across both scale-out database servers and scale-out intelligent storage servers, liberating database servers from processing low-level SQL statements for analytics queries so that they could process more OLTP queries and intricate analytics.
The Benefits of Exadata Cloud Infrastructure with AMD EPYC Processors
From our perspective, implementing Autonomous Database on Exadata Cloud Infrastructure delivers not only substantial performance improvements but also equally large economic benefits to customers. We see the higher levels of database consolidation enabled with Autonomous Database on Exadata as reducing the infrastructure requirements and associated costs needed to support a database fleet. Within this context, we view Oracle’s selection of AMD EPYC processors for powering Exadata database servers in OCI as a major contributing factor in optimizing these capabilities.
Beyond Oracle Data Platform
While Oracle offers a compelling set of data platform capabilities and benefits, we would be remiss not to mention other Oracle offerings that extend the value of Oracle Data Platform. From an overall cloud perspective, we have witnessed the level of functionality available in OCI grow into a robust offering that meets organizational needs for full-stack solutions and provides leadership capabilities in critical areas. Oracle’s growth rate in terms of adding new cloud functionality is unrivaled in the industry and includes multi-cloud connections with Azure and AI/high-performance computing (HPC) capabilities with NVIDIA.
Key Takeaways: The Enterprise-Wide Benefits of a Comprehensive Data Platform
We recommend that database and IT decision makers rank Oracle Data Platform high on their consideration list when looking at data platforms. They should compare Oracle Data Platform to data platform offerings from AWS, Microsoft, Snowflake, and others to see how they stack up in their ability to support diverse workloads with high availability. We also suggest that they carefully evaluate where they need to run their workloads to determine whether the platforms that they are considering can meet their data residency and isolation requirements.
We also suggest that chief sustainability officers and those considering the environmental impacts of their decisions carefully consider how Oracle Data Platform and OCI can help them meet their environmental impact goals with more efficient database consolidation and Oracle’s commitment to use 100% renewable energy in OCI by 2025—a goal they have already achieved in Europe.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Oracle Autonomous Data Warehouse: Boosting the Multi-Cloud and Open Source Missions
Oracle Database Analyst Summit: Powering the Multi-Cloud Era and Liberating Developers
Oracle Cloud Infrastructure: New Features and Database Portfolio Capabilities Boost Market Momentum
Author Information
Ron is an experienced, customer-focused research expert and analyst, with over 20 years of experience in the digital and IT transformation markets, working with businesses to drive consistent revenue and sales growth.
He is a recognized authority at tracking the evolution of and identifying the key disruptive trends within the service enablement ecosystem, including a wide range of topics across software and services, infrastructure, 5G communications, Internet of Things (IoT), Artificial Intelligence (AI), analytics, security, cloud computing, revenue management, and regulatory issues.
Prior to his work with The Futurum Group, Ron worked with GlobalData Technology creating syndicated and custom research across a wide variety of technical fields. His work with Current Analysis focused on the broadband and service provider infrastructure markets.
Ron holds a Master of Arts in Public Policy from University of Nevada — Las Vegas and a Bachelor of Arts in political science/government from William and Mary.
