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

Upcoming Webinar: Reviewing the Latency Landscape and the Next Generation of Ultra-Low Latency Infrastructure

Date: 17 September 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Ultra-low latency is no longer the preserve of a handful of proprietary trading firms. As new asset classes electronify, data volumes surge, and regulatory expectations around execution quality and resilience tighten, the performance demands on trading infrastructure are broadening...

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

RegTech Summit London

Now in its 10th year, RegTech Summit London will bring together the RegTech ecosystem to explore how the European capital markets financial industry can leverage technology to innovate the compliance function and response.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...