Big data is the core of your new enterprise application architecture. In the broader evolutionary picture, analytics and transactions will share a common big data infrastructure, encompassing storage, processing, memory, networking and other resources. More often than not, these workloads will run on distinct performance-optimized integrated systems, but will interoperate through a common architectural backbone.
Deploying a big-data infrastructure that does justice to both analytic and transactional applications can be challenging, especially when you lack platforms that are optimized to handle each type of workload. But the situation is improving. A key milestone in the evolution of big data toward agile support for analytics-optimized transactions is today, October 9, 2012, with the release of IBM PureData System. This is a new family of workload-specific, hardware/software expert integrated systems for both analytics and transactions. IBM has launched workload-optimized new systems for transactions (IBM PureData System for Transactions), data warehousing and advanced analytics (IBM PureData System for Analytics), and real-time business intelligence, online analytical processing and text analytics (IBM PureData System for Operational Analytics).
What are the common design principles that all of the PureData System platforms embody, and which they share with other PureSystems solutions? They all incorporate the following core features:
- Patterns of expertise for built-in solution best practices: PureData System incorporate integrated expertise patterns, which represent encapsulations of best practices drawn from the time-proven practical know-how of myriad data and analytics deployments. PureData System are built upon pre-defined, preconfigured, pre-optimized solution architectures. This enables them to support repeatable deployments of analytics and transactional computing with full lifecycle management, monitoring, security and so forth.
- Scale-in, out and up capabilities: PureData System support both the "scale-out" and "scale-up" approaches to capacity growth, also known as "horizontal" and "vertical" scaling, respectively. They also incorporate "scale-in" architectures, which allow you to add workloads and boost performance within existing densely configured nodes. You can execute dynamic, unpredictable workloads with linear performance gains while making most efficient use of existing server capacity. And you can significantly scale your big data storage, application software and compute resources per square foot of precious data-center space.
- Cloud-ready deployment: PureData System provide workload-optimized hardware/software nodes that are building blocks for big-data clouds. As repeatable nodes, they support cloud architectures that scale on all three "Vs" of the big data universe--volume, velocity and variety--and may be deployed into any high-level cloud topology (centralized, hub-and-spoke, federated, etc) either on your premises or in the data center of whatever cloud, hosting, or outsourcing vendor you choose.
- Clean-slate designs for optimal performance: PureData System incorporate "clean-slate design" principles. These allow us to to optimize and innovate in the internal design of each new integrated solution, improving performance, scalability, resiliency and so forth without being constrained by the artifacts of older platforms. When we think about the insides of our boxes, we're always thinking outside the box.
- Integrated management for maximum administrator productivity: PureData System incorporate unified management tooling and expertise patterns to enable low lifecycle cost of ownership and high administrator productivity. The tooling automates and facilitates the work of human administrators overseeing a wide range of workload management, troubleshooting and administration tasks over the solutions' useful lives. As workload-optimized systems, these solutions embed integrate expertise patterns that automate and optimize the work of human administrators.
Taken together, these principles enable the PureData platforms to realize fast business value, reduce total cost of ownership, and support maximum scalability and performance on a wide range of analytics and transactional workloads. These same principles are also the architectural backbone for the recently released IBM PureApplication Systems and IBM PureFlex Systems platforms.
Looked as a comprehensive business application platform, the PureSystems family unites analytics, transactions and middleware technologies within a converged architecture.