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: Enhancing trader efficiency with interoperability – Innovative solutions for automated and streamlined trader desktop and workflows

Traders today are expected to navigate increasingly complex markets using workflows that often lag behind the pace of change. Disconnected systems, manual processes, and fragmented user experiences create hidden inefficiencies that directly impact performance and risk management. Firms that can streamline and modernise the trader desktop are gaining a tangible edge – both in speed...

BLOG

Exegy Acquires NovaSparks to Accelerate Convergence at the FPGA Layer

Exegy, the low-latency market data, trading, and execution technology provider, has agreed to acquire NovaSparks Inc., the specialist in Field Programmable Gate Array (FPGA) enabled market data and trading products. Exegy’s move to bring NovaSparks into the group signals a clear intent to exert deeper control over the FPGA-driven market data pipeline, from normalisation and...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

Managing Valuations Data for Optimal Risk Management

The US corporate actions market has long been characterised as paper-based and manually intensive, but it seems that much progress is being made of late to tackle the lack of automation due to the introduction of four little letters: XBRL. According to a survey by the American Institute of Certified Public Accountants (AICPA) and standards...