Actian Vectorwise
Company Size
1,000+
Region
- America
Country
- United States
Product
- Actian Vectorwise
Tech Stack
- SQL
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Predictive Maintenance
Services
- Data Science Services
About The Customer
The Rohatyn Group (TRG) is a hedge fund headquartered in New York, focusing on emerging markets. The company provides analysts with immediate access to the information they need in a format that they can use through a self-service data access environment. TRG maintains extensive data about the current state of all their market positions in a multi-dimensional data structure managed by a proprietary in-memory database. This enables analysts to interactively answer their questions about the current state of their investments.
The Challenge
The Rohatyn Group (TRG), a hedge fund based in New York, needed a solution to manage risk in the highly volatile market of hedge funds. Information about positions, pricing, and risk is critical to investment decision-making. For tactical decision-making, TRG provided analysts immediate access to the information they needed in a format that they could use through a self-service data access environment. However, the combination of market volatility and a desire to do more strategic analysis drove the need to understand how their positions had performed over time. While the existing solution provided the interactive analysis TRG was looking for, it did not have the historical data. They wanted the user tools to remain the same and the query responses to be interactive, but they needed to do the analysis on more than 1000 times the data.
The Solution
TRG deployed Vectorwise to process data from multiple systems so that hedge fund managers could evaluate their positions in near real time. For the Vectorwise POC, TRG decided to flatten all of the data into a single table with almost 300 columns. They loaded millions of rows of historical data into the single table and the results were incredible. Vectorwise provided the in-memory performance and interactivity wanted with the data residing on-disk. Fast performance was delivered out-of-the-box without any indexing, preaggregating results, or extensive database tuning. Vectorwise’s support for standard SQL made the implementation very fast and the simplicity of the data design made the migration very easy.
Operational Impact
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