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 Pushes Hadoop Towards Low-Latency for Real-Time Analytics

Subscribe to our newsletter

OK, so the headline is a tad extreme, but bear with me. Recent developments combining in-memory technologies and Hadoop/MapReduce from ScaleOut Software point to a future where big data analytics and real-time processing, as it’s defined in the financial markets, could meet.

ScaleOut has just released its ScaleOut hServer V2, an in-memory data grid, which it claims can boost Hadoop performance by 20x, and can make it suitable for processing ‘live data’ to deliver ‘rea-ltime analytics’.

“To minimise execution time, ScaleOut hServer employs numerous optimisations to minimise data motion during the execution of MapReduce applications, and it can automatically cache HDFS data sets within the IMDG (a feature introduced with ScaleOut hServer V1). In addition, ScaleOut hServer’s memory capacity and throughput can be scaled by adding servers to the IMDG’s cluster. The product automatically rebalances the data set and execution workload when servers are added or removed,” says the company in a statement.

As well as boosting performance of a Hadoop deployment, hServer also incorporates Map/Reduce logic so that a Hadoop distribution is not actually required – though the company suggests its offering is not a direct replacement for Hadoop.

Nevertheless, “ScaleOut hServer is designed to be compatible with most Java-based Hadoop Map/Reduce applications developed for the standard Hadoop distributions, requiring only a one-line code change to execute applications using ScaleOut hServer.”

The big picture here is that ScaleOut – as well as other companies pushing in-memory technology – is recognising that the batch-oriented nature of Hadoop has limitations for real-time applications, such as those found in the financial markets.

While ScaleOut is today looking to boost Hadoop performance to make applications that used to take hours and minutes to execute run now in minutes and seconds, the performance trajectory could well follow that of the low-latency space, where milliseconds gave way to microseconds, and now nanoseconds.

The deployment of multi-core and multi-socket servers, GPU technologies and advances in memory will all benefit data grid vendors like ScaleOut, as well as Hadoop and other big data analytics offerings.

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

From Pilot to Production: Navigating GenAI’s Transition in Financial Markets

The financial markets sector is accelerating its engagement with generative AI (GenAI), yet moving from proof of concept (POC) to production remains a complex challenge. Key questions continue to dominate industry conversations: What use cases are mature enough for deployment? How can firms embed the necessary controls to manage reputational and regulatory risk? What organisational...

EVENT

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

Now in its 8th 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

Corporate Actions 2009 Edition

Rather than detracting attention away from corporate actions automation projects, the financial crisis appears to have accentuated the importance of the vital nature of this data. Financial institutions are more aware than ever before of the impact that inaccurate corporate actions data has on their bottom lines as a result of the increased focus on...