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Technology Convergence for
Intelligent Trading
Low Latency – Connectivity and Compute
Cloud – Managed, Hosted, On-Demand
Big Data – Analytics (Pre- and Post-Trade)
Combined, they will underpin much of the automated trading space
over the next months and years.
For many (most?), the latency race has finished.
Convergence Beyond the Financial Markets
“A paradigm shift is underway, as real-time data, rich analytics, and
robust cloud applications emerge”
- blog.gopivotal.com
Pivotal = Real-time, high capacity analytics in the cloud
(EMC, VMware, GE)
Hadoop, MPP Database, PAAS, In-Memory
Boosting Big Data Technologies
Lots of focus on improving performance of open source technologies,
such as Hadoop and Hive.
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Cloudera – Impala – high performance SQL for Hadoop
Pivotal HD – MPP/SQL/Hadoop Integration
Stinger – Hive SQL 100x – SAP, Facebook, Twitter, etc.
Intel Hadoop – Leverages specific Sandy Bridge features
NoSQL – R, Python, Q
In-Memory DBMS/Datagrids – SAP HANA, Terracotta, Cohesion,
ScaleOut, GemFire (now Pivotal)
• Software Defined Networks, Flash Memory
Cloud Coming of Age?
It’s All About The Economics Stupid!
• Continuing shift towards managed, hosted applications
• “Community Effect” driving location choice
• Big investments in cloud infrastructure – compute, storage, software
defined networking
• Virtualization performance improving
• Market Data Cloud paradigm
• App store paradigm, mobility
Back to Low Latency
Where are the next focuses?
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Wireless – making it more usable
Storage – Flash, DRAM, In-Memory
Network/messaging/application integration
Compute platform – processor and architecture choices
Time synchronization for trading
Software Defined Networks, Flash Memory
Application latency
Intelligent trading!