About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

ScaleOut Addresses Big Data In-Memory Analytics; Adds Multi-Site, Cloud Support

Subscribe to our newsletter

ScaleOut Software has released version 5 of its ScaleOut StateServer in-memory data grid.  For the first time, it supports linking grids across physical sites, including leveraging cloud services – providing an elastic architecture for big data analysis.  Version 5 is currently available for public clouds Amazon Web Services and Windows Azure.

“By helping developers and architects transparently access data from any networked data grid location, we can dramatically simplify their applications and create important new capabilities, such as seamlessly migrating application data into the cloud for processing,” says Dr. William L. Bain, Founder and CEO of ScaleOut Software.

Version 5 also introduces optimised, property-based query of grid-based data that can be performed directly from application programs.  The .NET community can use Microsoft’s Language Integrated Query (LINQ), and Java developers can use familiar filtered queries to programmatically access groups of related data within the grid based on selected criteria associated with the data.  This capability both simplifies the structure of queries and enables fast, parallel access from all grid servers.

In addition, property-based queries are now integrated into the ScaleOut MapReduce engine, making the selection of objects for analysis intuitive and straightforward for developers.  And a new columnar-based analysis capability has been added to enable efficient analysis and updating of a targeted set of large grid objects in a manner similar to running stored procedures in a database environment.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The Role of Data Fabric and Data Mesh in Modern Trading Infrastructures

The demands on trading infrastructure are intensifying. Increasing data volumes, the necessity for real-time processing, and stringent regulatory requirements are exposing the limitations of legacy data architectures. In response, firms are re-evaluating their data strategies to improve agility, scalability, and governance. Two architectural models central to this conversation are Data Fabric and Data Mesh. This...

BLOG

McKay Brothers Establishes Low-Latency London-Singapore Connection

McKay Brothers, specialist provider of low-latency network services for trading and market data distribution, has activated a new private transport service between London and Singapore with a round-trip latency of less than 137 milliseconds, aimed principally at firms trading cryptocurrencies and FX. “We continually evaluate where our services can add the most value for clients...

EVENT

Data Management Summit New York City

Now in its 15th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...