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

Data Platform Modernisation: Why The Hardest Problems Are No Longer Technical

Capital markets firms pursuing data platform modernisation have largely solved the technical challenges of compute and storage, but the organisational, governance and architectural decisions surrounding those platforms remain stubbornly difficult, according to practitioners from Northern Trust, RBC Wealth Management and LSEG, speaking at a recent A-Team Group webinar entitled Data platform modernisation: Best practice approaches...

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

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...