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GigaSpaces XAP Real-Time Analytics Solution

High Performance and Linear Scalability Without Increasing Complexity

GigaSpaces eXtreme Application Platform (XAP) supports real-time analytics with a single solution for managing the data, messaging, and business logic associated with a business transaction. Unlike multi-tier architectures that increase in complexity as they scale, GigaSpaces XAP simply and easily delivers limitless linear scalability and low-latency performance.

Business Challenge

Batch-oriented analytics applications in the middle office are being bombarded with enormous data volumes and the pressure to generate reports in near-real time continues to mount. Traditional approaches to analytical processing do not provide the linear scalability and high performance applications required to handle large sets of data in a short period of time. To meet extreme analytical processing demand, applications must be able to:

  • Scale quickly to support fast and unpredictable growth.
  • Handle exceptionally demanding requirements in complex, distributed environments including event-driven and Service-Oriented Architectures (SOA).
  • Ensure high performance at all times.

GigaSpaces XAP Provides

  • Speeds processing flow by holding data in memory and cuts contention through partitioning schemes
  • Virtualizes processing by load balancing and managing resilience across multiple nodes
  • Virtualizes the API stack to make it available to a wide range of legacy applications

Usage Scenarios

GigaSpaces eXtreme Application Platform (XAP) supports real-time analytics applications that require near real-time responses, including:

  • Algorithmic trading, risk and portfolio analysis, VAR Calculations, PNL, surveillance, compliance, and real-time regulation in the Financial Services industry
  • Fraud detection in the Telecom industry
  • Real-time intelligence analysis, homeland security, and civilian agency applications in Government organizations

Based on a Space-Based Architecture, XAP creates self-sufficient processing units that can scale-out across many cost-effective computers, allowing organizations to leverage investments in current systems while benefiting from the higher utilization and flexibility afforded by grid computing, SOA, and other highly distributed architectures.