Weka for Financial Analytics Improves Wall Clock Time

Companies are now applying predictive models for deeper insights and risk mitigation, and success is measured by the fast execution of algorithmic and deep learning model results. Weka is used by leading quantitative trading companies who are constantly seeking out new advanced technologies to gain a competitive advantage and improve trading outcomes. Financial analytics requires a modern storage architecture that can handle the most demanding I/O intensive workloads and latency-sensitive applications at petascale. Weka has demonstrated record-breaking performance on STAC M3 benchmarks using kdb+ time-series database.

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Weka offers kdb+ a combination of good read performance and metadata operational latency, being one or two orders of magnitude better than EFS storage gateways and all open-source products we tested

Glenn Wright, Systems Architect, Kx Watch Webinar
6 Reasons to Deploy Weka in Your Financial Services Environment
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Delivers Higher Performance Than Local-Drive SSDs

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Enables Elastic Public Cloud for Peak Compute Demand

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Single Storage Platform for Entire Dataset

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Dramatically Improves Wall Clock Time

Exscale Capacity

On-Demand Scalability and Economy

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Best TCO Leveraging NVMe for Performance and HDD for Capacity

WekaFS for Financial Analytics - STAC-M3 Benchmarks Overview Video
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WekaFS for Financial Analytics - STAC-M3 Benchmarks Overview Video

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Weka for Analytics and Financial Modeling
Use Case

Weka for Analytics and Financial Modeling

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Top 5 Reasons Why WekaIO for Financial Services
Solution Brief

Top 5 Reasons Why WekaIO for Financial Services

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