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Oracle Big Data SQL on Dell EMC PowerFlex
Executive summary Business case Use case overview Oracle Big Data SQL architecture Storage design Lab validation of Oracle Big Data SQL data virtualization Testing Oracle Big Data SQL data virtualization Summary
Summary
References

Summary

Summary

  • Oracle Big Data SQL fits well into an enterprise that has a foundation of Oracle experience. For example, teams working on mining big data can accelerate analysis through Big Data SQL data virtualization. As this solution shows, the steps to connect disparate systems are definitely manageable. Querying the data only requires writing SQL. Choosing use cases that can be achieved in a short time provides a pathway to early wins for the enterprise. The ability to achieve an early win was demonstrated in this solution because the data sources that we used had access drivers or were configured with Oracle Database Gateways.

    Building on early wins means the enterprise can use Oracle Big Data SQL experience as a foundation for more comprehensive data analytics initiatives. These key factors will influence broader adoption of data analytics using Oracle Big Data SQL.

    • Fast access to other disparate resources—One of the cornerstones of data virtualization is the capability to quickly connect to other systems. In this solution, we used Microsoft SQL Server to determine if connecting to resources that had no Oracle Big Data SQL access driver was relatively seamless. Lengthy and complex processes for connecting to heterogeneous data sources detract from the value of data virtualization. In this solution, using Oracle Database Gateways streamlined accessing the Microsoft SQL Server database.
    • Accessing various disparate resources—For data virtualization to be successful, the platform must support numerous disparate resources. Oracle Big Data SQL supports Apache Hadoop, Apache Kafka, ONDB, object stores, and through Oracle Database Gateways, other data sources. A key recommendation to selecting a data virtualization platform is to map the data sources with the access methods to understand capabilities, complexities, and cost.
    • Analytics tools—Oracle 19c, part of Big Data Clusters, has integrated analytic capabilities for developers. Tools like Python, R, Scala, and others were not used in the scope of this solution. However, it is critical that the tools that developers are using today are available to support ongoing analytic programs. The recommendation is to include a list of analytic tools required for the data virtualization platform.

    The final consideration is the adoption of an agile data virtualization and analytics infrastructure. In the case of the solution architecture proposed for this Oracle Big Data SQL platform, our key goals were to achieve rapid build out, multisource data placement, and design for expansion of the system. The combination of the PowerFlex system and VMware virtualization maximized agility of the data virtualization platform and the ability to scale it up or down on-demand. The PowerFlex system enables a modern, network-based blended architecture of dedicated PowerEdge servers for Oracle and Microsoft SQL Server databases and a hyperconverged platform for Cloudera Hadoop and NoSQL databases.

    Because this Oracle Big Data SQL solution is based on servers for dedicated computing and storage, the ability to rapidly address growth is significantly simplified. The capability to rapidly address expansion of one part of the data virtualization platform means that the enterprise can optimize investment. For example, if additional storage capacity and performance is required, adding PowerFlex nodes addresses the growth requirement. Conversely, if dedicated compute is needed for additional databases, the business can rapidly address the expansion. 

    The agility of this Oracle Big Data SQL solution means that architects can dynamically build the data virtualization platform over time. The planned expansion approach reduces risks for the enterprise. Architects and developers are challenged to deliver a comprehensive solution architecture that addresses performance over two to three years; this solution meets that challenge.

    Another key benefit is the capability to incrementally update the data virtualization platform with infrastructure and software advances. Advances in processors and storage technology can be realized almost immediately by seamlessly adding new PowerEdge servers or PowerFlex nodes to the platform. The challenges associated with large metal upgrades or highly integrated systems are not factors in this agile platform approach.

    Transformation to an Oracle Big Data SQL platform enables the business to embrace data virtualization and enhances the possibility of achieving quick wins on analytic initiatives. When combined with this Dell Technologies platform, the enterprise can achieve a highly agile platform that enables optimal expansion.