Try before you buy. See how IBM Spectrum Computing reduces costs and accelerates time to results.

Build your big data strategy on a solid foundation

IBM Spectrum Computing software is designed to maximize analytics performance while reducing your costs.

You gain a low-latency solution for heterogeneous application integration on a shared multi-tenant architecture.

This high-performance foundation empowers you to accelerate performance-intensive analytics and machine learning. Discover how IBM Spectrum Computing can help you capitalize on the full value of your big data.

Analyze data and extract insights quickly and economically

IBM Spectrum Symphony Advanced Edition

Gain enterprise-class management for distributed compute- and data-intensive applications, including Hadoop MapReduce. This software is designed to deliver high resource availability and predictability, support for multiple applications and file systems, operational maturity, SLA policy control, and extremely high resource utilization.

IBM Spectrum Conductor with Spark

Simplify Apache Spark deployments, speed time to results and maximize resource utilization. This end-to-end solution for deploying and managing Spark applications is designed to help you adopt Spark technology for your big data analytics requirements.

IBM Spectrum Computing resource scheduling

This resource scheduling software employs optimization techniques that allow sub-millisecond response and fast provisioning for a variety of workloads. As a result, short-running jobs spend a smaller percentage of time in the provisioning and deprovisioning steps, giving a higher useful work-to-overhead ratio. IBM Spectrum Symphony has a high job throughput rate that allows more than 17,000 tasks to be submitted per second.

Take control of complex, distributed big data workflows

Optimize utilization

Policy-driven workload scheduler provides better granularity and control

Pool compute resources

Multiple instances of Hadoop, Spark and other applications can run on a single shared cluster

Speed time to insights

Distributed runtime engine supports high resource availability

Increase efficiency

Flexible, open architecture supports application development and choice of file system

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