Rebar's Data Virtualization Engine

Virtualized Data Maximizes the Value and Efficiency of Client Systems

​Due to market complexity and time to market requirements organizations turn to kneejerk solutions, often provided by the various FinTech vendors.  In this type of an environment data consolidation is paramount. Data virtualization is the key enabler that makes this process possible.

What is data virtualization?

Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted or where it is physically located.

Unlike the traditional extract, transform, load ("ETL") processes, the data remains in place, and real-time access is given to the source system for the data, thus reducing the risk of data errors and reducing the workload of moving data around that may never be used.

Data virtualization does not attempt to impose a single data model on the data and it also supports the writing of transaction data updates back to the source systems.

The value of data virtualization is its ability to access, normalize and utilize disparate data without the time and expense associated with having to move and store that information. 

How does it works?

Rebar’s data virtualization engine (DVE) adds a virtual services and data abstraction layer to your existing IT architecture.  It enables integration to applications, databases or files and enables information from these disparate data sources in real-time, near real-time or batched as user requirements dictate.  The data is then available for use by new custom applications & modules, workflow management, business calculation & algos, GUIs or reports.  

Why use Rebar's data virtualization engine?

Many data products create large, normalized databases well suited for querying and reporting capabilities, however, in the financial technology space, they are not performant enough to act as a foundational layer for new applications, algorithms, or other performance critical functions.  Rebar's data virtualization technology was specifically created to service the high volume, low latency financial marketplace.

​Rebar’s event driven architecture and bi-direction data access capability allows us to quickly adapt disparate data sources and make them work well together to maximize and leverage your existing investment. This provides a robust foundation for new application development in addition to querying and reporting.  Rebar's virtualized environment is able to respond immediately to data changes or new information allowing for real-time querying, analytics calculations, alerting, etc. 

What can it be used for?

Because Rebar’s data virtualization architecture is data agnostic, it can be used in any number of ways.

• Support – Rebar’s DVE can capture and make available application health data including: hardware, memory and connection status, module or application state, sending commands and more.
• Trading systems – Rebar's DVE can be used in a number of trading areas including:
  1. Broker connectivity – Ingest real-time market data and perform analytics such as top of book and present results to trading applications
  2. Collect trading data across multiple trading systems necessary to view global blotters, view or calculate P&L, perform analytics, run risk controls, etc.
  3. And more. 
• Reporting and analysis – Collect disparate yet related information to create business intelligence reports

​What are the key business drivers for data virtualization?

• Increasing profits – Data virtualization delivers the data you need in real-time so that businesses can make time sensitive business decisions aimed at increasing revenue and reducing costs.
• Reducing risk – Consolidated views and analyses provide the information required to manage business risk, reduce compliance issues, and reduce IT project risk.
• Reducing cost and time to market – Data virtualization expedites application integration times relative to traditional warehousing approaches.
• Increasing efficiency – With all the necessary data normalized and available, data virtualization increases IT and staff productivity.

Data virtualization architecture

Rebar’s data virtualization architecture combines SOA principles such as decoupling, reuse and agility with key information governance principles such as abstraction, shared semantic models and data standards.  Data virtualization’s loosely-coupled, highly-scalable approach to data integration adds flexibility to information architectures. 
Data virtualization can be deployed using a number of different options.  Common consolidation style architecture implementations include Virtual Data Marts and Virtual Data Stores.
Layered information architectures can also be implemented using data virtualization. Examples include:

• Data Abstraction Layer – is used to hide the complexity of disparate data silos that have their own access mechanisms, syntax, complex structures and security and provide a simple data access layer that both the business and IT can use.
• Data Service Layer – provides industry standard interfaces with common formats so that sharing data across myriad departments, partners, suppliers, customers and others is easily achieved
• Distributed data virtualization layer – allows for the implementation of the environment including all components to be distributed across any number of physical or virtual servers.  This allows true scaling, reduced risk of complete system failure, low latency performance tuning and more.
• Virtual data warehouse – data virtualization allows for cached data to behave like a traditional data warehouse without the associated performance inefficiencies and costs.  Rebar’s DVE allows for quick creation and modification of caches making data instantly available to any module, database or application subscribing to the data.  All caches may be instantly or periodically updated to stay synchronized with the golden sources of data.

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