About a-team Marketing Services
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: Navigating the Build vs Buy Dilemma: Cloud Strategies for Accelerating Quantitative Research

For many quantitative trading firms and asset managers, building a self-provisioned historical market data environment remains one of the most time-consuming and resource-intensive steps in establishing a new research capability. Sourcing data, normalising symbologies, handling corporate actions and maintaining infrastructure can take months and absorb significant budget before a single model is tested. At the...

BLOG

Determinism is the New Speed: Why High Performance Trading Infrastructure is Being Redefined Around Provability

The definition of high performance in trading infrastructure is shifting. Raw speed, once the key benchmark, is increasingly being subsumed into a broader set of requirements around determinism, provability and architectural simplicity. For firms operating in fragmented, event-driven and increasingly automated markets, the competitive edge is no longer measured in nanoseconds alone, it lies in...

EVENT

Eagle Alpha Alternative Data Conference, Spring, New York, hosted by A-Team Group

Now in its 9th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Regulatory Data Handbook 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...