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The FAME software environment had several development phases during its long history.
Lawrence C. Rafsky founded GemNet to create FAME in 1982. It was an independent software company located in Ann Arbor, Michigan. The first version of the software was delivered to Harris Bank in 1983. The company was purchased by CitiCorp in 1984. During this time, development focused on the time series oriented database engine and the 4GL scripting language.
Citigroup sold FAME to private investors headed by Warburg Pincus in 1994. Management focused on fixing bugs, developing remote database server access to FAME, and invested in expanding the FAME database engine. Emphasis was also placed on extending FAME by creating an object-oriented Java interface called TimeIQ that replicated many features of FAME 4GL in Java. This period also saw the release of accessPoint, which provides URL access to FAME objects in multiple output formats.
- Modernizing the connections into the FAME database environment for better integration with other software
- Support for service-oriented architectures (SOA) via the FAME Web Access middleware server
- Creating workflow-oriented dashboards and wizards for extracting, transforming and loading data into FAME databases
- Improving querying tools, including connectors to third-party applications
- Extending managed content, including tools for building metadata on top of FAME databases
Another key goal has been to modernize the tools that support working in the FAME software environment. For example, developers have worked to leverage FAME Web Access and transform FAME into software that can be run as a service. This allows developers and architects to plug the online analytical processing capabilities of the FAME software into existing enterprise software and empower these internal systems to better handle the complex queries made by financial professionals.
Many FAME customers run the environment within an overall technology stack, providing improved access and wider distribution of data and analytics. Rather than access standalone FAME installations, these enterprise-oriented technology teams load FAME databases and procedures within a Multiple Client Analytical Database Server (MCADBS), providing access to FAME data via browser applications, Microsoft Excel, statistical applications and advanced reporting systems such as Crystal Reports.
Fully-managed content service
Early in FAME’s evolution, customers who obtained loaders from the company were required to build and maintain their own processes for loading vendor feeds. SunGard provides a service that delivers content throughout the day to FAME SiteServer, FAME Channel, and FInDS.
Toolkits and connectors
FAME Desktop Add-in for Excel: FAME Desktop is an Excel add-in that supports the =FMD(expression,sd,ed,0,freq,orientation) and =FMS(expression,freq + date) formula, just as the 4GL command prompt does. These formulas can be placed in Excel spreadsheets and are linked to FAME objects and analytics stored on a FAME server. Sample excel templates for research and analytics, which act as accelerators for clients, are available in the template library.
FAME Connector for MATLAB: Matlab is an environment for technical computing applications that is also used in the financial sector by fixed income analysts, equity research groups and investment firms. Customers can store content in FAME and use Matlab to access and model their data. The Matlab-FAME Connector uses the FAME Java Toolkit to link Matlab scripts to FAME objects.
BITA Curve Connector: The BITA Curve workstation provides a platform that can link to “in database” analytics and content warehoused in FAME. Through the BITA Curve Connector, FAME users can better visualize and work with the content that they warehouse into FAME.
R Interface: FAME customers have developed and released as free software an interface that links FAME objects to the open source R statistical package. Originally developed at the Federal Reserve Board, features include:
- Time series adaptation of FAME to R
- Frequency conformance
- A set of fundamental statistical functions
SASEFAME: SAS provides an interface to FAME databases called SASEFAME. This provides dynamic read and write access between a SAS application and FAME databases or a FAME server process
TROLL Interface: TROLL’s interface to FAME provides read and write access from a TROLL application to a FAME Server or directly to a local FAME database
1982–1994: GemNet introduced the first release of FAME in 1983. CitiCorp purchased the company in 1984. Development milestones during this period:
- 1990: First FAME Remote Database Server (FRDB) – master/dbback – released
- 1991: Data distribution services launched
- 1993: Multiple Client Analytical Database Server (MCADBS) released with FAME 7.5
Before MCADBS, users could not use a thin C HLI client to leverage the power of 4GL on a remote host via client/server TCP. The 7.5 release also introduced some important 4GL features, including PostScript Reports, and database features such as global names and formulas.
- 1994: FAME 7.6 made graphical and reporting enhancements as well as performance improvements.
- Mid-1990s: Standard & Poor’s, Thomson Financial, DRI and FT Interactive Data product loaders created
1994–2004: During this period, the focus was on improving managed content delivery to onsite FAME warehouses and hosted ASP FAME servers. Milestones included:
- 1997: MSCI and Russell product loaders added
- 1998: FAME 8.0 with FRDB write server released
- FAME Populator 4.0 released
- TimeIQ (now known as FAME Java Toolkit) beta 1 released. FAME created an object-oriented Java programming interface.
- 2001: FAME 9.0 increased the FAME database size limit from 2GB to 64GB.
- 2002: FAME 9.0 for Windows released
- 2003: FAME 9.0 ported to Linux
- 2004: accessPoint (now known as FAME Web Access) with connection pooling released
2004–present: After being acquired by SunGard, FAME’s development focus shifted to the 4GL scripting language and core FAME features. Milestones included:
- 2004: accessPoint 1.5 released
- August 2005: Enterprise FAME Java Toolkit 2.2 released
- December 2005: referencePoint launched
- March 2006: Support for 64 bit Linux and UNIX introduced in FAME 9.2
FAME 9.2 also added new 4GL debugging features, analytical functions, graphics and reporting improvements. Other core 4GL features included the MOVE function and new forms of the SHIFT and FILESPEC functions. The FAME SEARCH command was enhanced with the PATH option. Support for memory mapped FAME databases and TUNE CACHE MEGABYTES option helped users to better manage large volume warehouses.
- 2007: Pathfinder Global Formula run-time beta tested
- June–September 2007: FAME 9.3 added new debugging features, including the DEBUG option and BREAK, STEP and CONTINUE commands.
FAME 9.3 also introduced new graphical features, including BUBBLE charts.
- February 2008: accessPoint 1.7 with Web Services released
- May 2008: SiteServer on Linux released
- October 2008: FAME .NET Toolkit released
- February 2009: FAME 10.0 released.
FAME 10 opens up the environment to real-time analysis with larger database storage, as well as support for new frequencies, such as millisecond and weekly patterns. New database formats increase maximum size to 256 GB.
During this period FAME has also focused on expanding the managed content delivered to the database, as well as out-of-the-box object models that warehouse builders can leverage when loading proprietary content.
- Expanded managed content provides out-of-the-box data and object models for:
- Equity pricing
- Corporate bond pricing
- Futures, commodities and options
- Company and index fundamentals
- Company and index estimates
- Macro-economic indicators and benchmark construction
- FAME 10 provides a number of enhanced features for creating object models, including
- Support for longer object names (up to 242 characters) and for assigning unlimited number of user-defined attributes to an object
- Support for object names with up to 35 dimensions
- December 2010: FAME 10.1 released.
- December 2011: FAME 10.2 released.
- March 2012: FAME 11.0 released.
- June 2012: FAME 11.1 released.
- December 2012: FAME 11.2 released.
- March 2013: FAME 11.3 released.
- June 2014: FAME 11.4 released.
- November 2015 : FAME 11.5 released.
- "SunGard to Acquire FAME; Adds Reference Data Solutions to its Market Data Offerings". December 5, 2003.
- Hallman, Jeff (July 12, 2015). "fame: Interface for FAME Time Series Database". Retrieved July 24, 2015.