Company name: DataDirect Networks (DDN)
Company website: www.ddn.com
Nature of business: DataDirect Networks (DDN) is the world’s largest, privately-held, data storage provider. With a unique and exacting focus on the requirements of today’s massive unstructured data generators, DDN has innovated a comprehensive product portfolio for Big Data and cloud applications, which are optimised for the world’s most data-intensive environments, including financial services.
DDN’s portfolio of products includes web-scale storage array, file system and object storage appliances. These scalable and highly efficient storage solutions enable its customers to accelerate time to results, scale simply as data sets continue to grow and gain competitive advantage through resolving performance and capacity scaling challenges. By optimising each element of the I/O environment for performance, capacity and data centre efficiency – DDN solutions deliver the highest levels of ROI as businesses achieve more with purpose-built tools for data-intensive applications.
Locations/also markets they operate in: With over 500 employees, DDN has a worldwide presence in over 20 countries with office locations in The Americas, Europe, Middle East and Africa (EMEA), Asia, India & South Pacific
Branch locations: UK, Australia, France, Germany, Ireland, Japan, UAE and USA
Alex Bouzari, CEO, Chairman & Co-founder
Joseph L. Cowan, President
Jeff Denworth, VP, Marketing
Chris O’Meara, CFO
Brief history of the company: Established in 1998, in many ways, DDN has been mastering Big Data challenges before the term ‘Big Data’ was even invented. By supporting the requirements of the world’s largest file storage systems and data intensive applications for over 15 years, DDN has developed both domain expertise and an unique advantage in helping solve the storage challenges associated with massive data growth making DDN the top choice for storage among the fastest computers in the world.
In Financial Services, data capture, algorithmic development, back testing, risk management and fraud detection functions are pushing the boundaries of performance of current storage infrastructure. By using fast, scalable, external disk systems with massively parallel access to data, researchers can perform analysis against much larger data sets delivering more effective models, faster.
Some examples include:
Innovative, award winning and proven in the world’s largest and most demanding production environments, DDN Storage Fusion ArchitectureTM (SFATM) delivers enough power to improve modeling performance, especially for problems that exceed cache size. Any time a modeling data set exceeds cache, data access to traditional storage (with low parallelization and high interrupts on spinning disk) causes performance to drop significantly. DDN’s massive parallelization delivers the performance to run hundreds of model iterations in the same time it takes to run several sequentially in cache today.
The DDN SFA is software-based and uses highly parallelized storage processing to deliver industry-leading IOPS and massive throughput at the same time. SFA was built from the ground up for speed. Implemented in user space, SFA is a state machine, controlling all interrupts to the kernel rather than the other way around. By taking this approach, SFA completely controls quality of service and can consistently deliver performance, even under outage conditions that would fail or seriously degrade other storage systems.
DDN recently completed a series of market data and analytics benchmark tests, created and audited by the independent Securities Technology Analysis Center (STAC). The results show that DDN storage systems deliver:
- Up to 8 times faster than traditional storage and up to 2 times faster than flash
- Improved Post-Trade analytics, such as a market snapshot, up to 70% faster
- Accelerate Research Analytics for tasks such as market statistics analysis by 100%
- DDN achieves faster analytics results from servers with 1/2 the cores and 1/2 the memory by using faster storage
- Improves analytics server efficiency to cut the number of analytics licenses in ½ while delivering better response times