The Real Time Market Data Server by Modulus Financial Engineering

The perception of speed is relative to the perspective of the observer.
-- Unknown

RMD Server Desktop Edition
Scenario: You have a Desktop trading application that uses one or more data vendors such as E-Signal, DTN, and NAQ. You would like to work with just one interface for simplicity, and be able to request secondly, minutely, and daily bars with ease. You need a database system that is easy to setup and maintain, and cost effective.

RMD Server Enterprise Edition
Scenario: You have multiple data feeds from sources like DTN, Bloomberg and various exchanges. You would like to rebroadcast data to multiple clients over a network, store data in a centralized location, and handle administration on all accounts, restricting individual user logins to specific symbol groups, login permissions, account expirations and more... in short, you need a complete ticker plant from the ground up.

  View the RMD Server Documentation

There is no question that the computer has radically enhanced our ability to perform time series analysis (TSA) in a, well, timely manner.  The manual collection and plotting of thousands of data points could take weeks in the pre-PC days.  Now our computers can crunch numbers and produce results in hours, if not minutes.  Yes, to the casual observer it happens fast.  However, is fast actually fast enough when split-second market-timing decisions hang in the balance?  Ask any trader who has had to wait several minutes for decision support that was needed in several seconds, and you’ll begin to understand that the perception of speed truly IS relative to the perspective of the observer.

It’s hard to blame the average financial software developer for storing “data” in a “database”.  After all, isn’t that what a database is supposed to do, store data?  Any in-depth study of the method in which TSA results are obtained would reveal that a structured relational database is the last way that time series data should be stored.

"Having an RDBMS doesn't mean instant decision-support nirvana. As enabling as RDBMSs have been for users, they were never intended to provide powerful functions for data synthesis, analysis, and consolidation (functions collectively known as multidimensional data analysis)."

 - Ted Codd, inventor of the relational database model, 1993.

If the man who invented the modern-day computer database doesn’t think that it is suited for data analysis, why do we insist on storing data in them?  Simple – until now, there has been no better solution.

A look at traditional data storage

SQL databases consist of a set of row/column-based "tables", indexed by a "data dictionary".  A table is a “container” that stores data. In reality, a table looks a lot like a spreadsheet as it is composed of rows (records) and each row is composed of columns (fields).  A collection of related tables are known as a database.

Using the very flexible SQL (structured query language), you can retrieve data from any table, or groups of related tables, and have that data presented to you as a “view”.

This basic functionality, and the flexibility to store and relate almost anything, is what makes the RDMS model so powerful and so widely used for nearly every serious business application.

Unfortunately, this “one size fits all” approach to data storage and retrieval is exactly why the RDMS model fails so miserably for financial analysis and reporting applications.

The RDBMS model produces substantial overhead due to its inherent multiple row and table record structures. When you heap indices, clusters, and procedures on top, you create even more overhead which slows down performance considerably.

Since all RDBMS records are equally “important” to the database, they are not optimized for speed.

Also, since an RDBMS has no inherent data compression methods, they are usually combined with exception reporting and averaging techniques, which may result in data loss and inaccurately reproduced data.

RDBMS Are Too Slow

The speed of writing to an RDBMS is quite slow (from the prospective of the PC).  Major RDBMS vendors often claim benchmarks that include very high transactions per second (TPS).  What they don’t say is that the TPS speed refers to actions performed on the data after it is already in the database, and not to the speed at which it is written to the database or the data retrieval speed.  What goes on inside of the database is of little interest to the end user.  The data acquisition speed, and the actual time that it takes to put a set of results onto the screen, is where money is made and lost.

An additional SQL drawback, from the prospective of any financial-based data reporting, is that statistics are not automatically calculated by the RDBMS because SQL mathematics is limited to sums, minimums, maximums, and averages.

What’s more, a traditional RDBMS is generally limited to a one-second-time resolution.  This is a problem when you are acquiring high burst quantities of data with sub second time stamps.

The ideal solution for the financial industry is a storage and retrieval methodology that is able to accesses data extremely fast, nearly instantaneously, and can calculate the statistics for a given time span "on the fly" without the overhead of a RDBMS.

 
The solution is Modulus Financial Engineering’s Real-time Market Data Server (RMD Server™)

RMD Server : A new data retrieval methodology custom-designed from the ground up for financial analysis.

RMD Server uses a new generation of data storage specially optimized for the financial analysis industry.

The heart of RMD Server is our new patent-pending search algorithm, JADE™. RMD Server is capable of scanning through terabytes of data (1024 gigabytes) in search of a specific time series record at up to hundreds of times faster than the fastest known RDBMS in existence.

“Our innovative JADE search algorithm enables RMD Server to outperform industry standard RDBMS products like SQL Server by many times in terms of speed and efficiency for time series analysis"  - Tom Wong, Senior Software Engineer at Modulus Financial Engineering.

In the financial industry, where fortunes are made and lost in a blink of the eye, and the perception of speed truly is relative to the perspective of the observer, RMD Server has raised the bar beyond the reach of any traditional RDBMS system available today.

RMD Server is available as a stand-alone server product that may be used within most development languages, including C++, VB, Delphi, VB.net, C#, and Java, via the included Application Programmers Interface (API). 

Features

Easy Setup
RMD Server is easy to deploy. A database installation wizard guides you through the setup process and sets up your databases automatically. The Desktop Edition is easy to
redistribute, with only one configuration file to setup.

Example Application Support
RMD Server comes with example applications to get you started quickly. You can develop and maintain a complete data service, with data subscriber administration, access restrictions based on symbol groups, account expiration management, and more.

Administration
The RMD Server Administrator enables you to easily manage your RMD Server. Using the built-in features, you can perform the following:

• Create and edit databases in RMD Server
• Manage logins (admin or remote users / data subscribers)
• Perform ad-hoc queries and output the results

With RMD Server Desktop Edition, you can aggregate data feeds into one database, perform time series analysis and update data in real time.

RMD Server Enterprise Edition is designed for enterprise scale database applications such as powering a ticker plant or managing data for financial web sites. This version is licensed on a per CPU basis.

Hardware
We also provide inexpensive data servers for enterprise financial applications. Our servers are built to specification. Two terabyte models start at $5,200, and six terabyte models start at $13,400. Contact us for details at (888) 318-3754

System Requirements
Windows 2000, Windows 2003 Server, or Windows XP
Microsoft Internet Information Services (IIS) for Web Administrator Service

 

 

Copyright ® 1999 - 2008 Modulus Financial Engineering, Inc.