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Success stories.
Read about how some of our customers have increased their ROI using kdb+.
- 1010data
- Appian
- First Derivatives
A 40-year veteran of the technology and financial services industries, Joel Kaplan has a pedigree that includes stints at IBM, UBS North America, and Morgan Stanley, where he gained renown for leading the first team to employ scientific methodologies to uncover and exploit inefficiencies in the stock market. Today, as Chairman, CTO, and co-founder of 1010data, the leading provider of cloud-based analytics for Big Data, Joel is widely recognized as an industry leader in the use of technology on Wall Street and beyond.
Joel’s pedigree also includes an intimate connection with the technology behind Kx Systems, as he worked closely at Morgan Stanley with Arthur Whitney, co-founder and Chairman of Kx, who built the programming platform that eventually led to the development of Kx’s robust database products. In fact, at the beginning of Joel’s tenure at UBS, he convinced the company that if it wanted to be a leader, it had to use Arthur’s very special technology — the same platform that 1010data uses today to build extremely fast and powerful analytical solutions for its clients.
“What makes Kx technology so unique,” says Joel, “is that it requires a certain geometric intuition. Those who can take advantage of it are rewarded with the absolute fastest technology in the world. And, because the idea of linking tables across billions of rows of data is the same in any industry, this technology has applications that go far beyond any particular market or analysis.” The proof? One need only look at 1010data’s large client list of well-known, global enterprises in retail, manufacturing, and telecommunications.
Joel sees Kx technology as the vanguard of a third major tradition in the history of computing. Following the initial, groundbreaking work of Gödel, Turing, and Von Neumann that resulted in languages such as Fortran and C, and the subsequent functional school of logical programming behind Alonzo Church, which spawned LISP and other AI languages, Kx’s contemporary k and q languages represent today's natural evolution of the array oriented, vector programming work of Kenneth Iverson’s APL.
“In addition to the flexibility and versatility of vector languages,” notes Joel, “Kx's technology has another important advantage. It allows you to show your clients what’s possible using their own data. You can actually demonstrate to them how their problems can be solved, instead of asking them for a leap of faith based on extrapolating from generic benchmarks. The value of this cannot be overstated.”
Joel also appreciates the ongoing communication he has with the Kx Systems’ team, in which improvements to the technology — increasing speed, for example, or creating routines to improve certain functionality — come from both sides, ultimately allowing him to offer his customers cloud-based solutions of extreme robustness and expressiveness.
Because of his deep involvement and impact in the field over the past four decades, Joel understands the pressures on IT departments to shy away from such disruptive technologies as Kx. When it comes to increasing productivity, however, he believes there is simply no other way to go.
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With its roots in the fields of Business Intelligence and Data Warehousing, Appian Corporation knows what it takes to work with companies having large-scale database applications.
That’s why, in 2001, after one of its founders read an article in Wired magazine, this market leader in the field of Business Process Management contacted Kx Software regarding kdb, its small-footprint database that could handle tremendous data volumes. It wasn’t long before Appian was embedding kdb as a platform for building solutions for the company’s telecommunications, government, and financial services clients. Today, Kx technology is a core piece of Appian’s BPM Suite architecture, which helps clients rapidly design and execute repeatable processes — processes that are continuously subject to an enormous number of rules, regulations, and changes.
Appian saw kdb as a way to address fundamental problems in scaling out the query performance of large datasets that would allow it to deliver functionality to its customers that they couldn’t find anywhere else. The software turned out to be particularly suitable to the company’s expertise in BPM, where analytic queries and high-speed, real-time reporting are of critical importance.
The key, according to Appian, is the syntactic elegance, algorithmic performance, and simple, reliable construction of the Kx system. These technical advantages have created not only business possibilities for Appian, but a very real, and distinct, competitive advantage. Today, Appian uses the software in a wide variety of applications, from data storage, real-time analytics, and personalization to high-performance bulk updates to virtually every type of query, including time-series, OLAP, and hierarchical.
What’s more, the productivity of Appian programmers has improved significantly with kdb, as the integrated query language makes it easy to develop applications faster. Not only that, whenever an Appian coder has a question or problem, Kx has proven to be incredibly responsive, often returning a solution within hours.
At the beginning, Appian saw Kx as a visionary company. Yet even today, after a ten-year relationship, and with all of the dramatic improvements that have occurred in hardware and software, the company still hasn’t seen what it believes to be a comparable technology for solving this class of problems. read
As CEO of First Derivatives, a leading provider of software solutions and consulting services to the capital markets industry, Brian Conlon is as concerned with the technology that generates this information as with the information itself. This means — in addition to carrying out First Derivatives’ strategic plans, advising its various business groups, and directing its new business efforts — he’s actively involved in the design of the company’s business processes and high-level technology decision-making. And it’s in these latter two areas that Brian’s life has been made easier by Kx Systems.
“We were introduced to the original kdb in 1998,” says Brian, “and it didn’t take us long to appreciate that this was a special piece of technology. We decided early on that a key goal should be to establish the largest talent pool of kdb developers in the world.”
That talent pool was largely responsible for developing Delta Suite, the company’s data management and trading software, using kdb as part of the backbone of the product’s core offerings. Deployed in some of the world’s largest banks, exchanges, and hedge funds, Delta applications are designed for “volume and velocity”: low-latency, high-throughput applications delivered as a hosted service or deployed locally — from reference and market data management, CEP and exchange management and surveillance to treasury risk management and algorithmic, FX, and high-frequency trading.
In selecting kdb as its database of choice, Brian cites a prior knowledge of the product’s benefits: “We already had a clear understanding of kdb’s strengths over other database and in-memory engines from our involvement in numerous proof-of-concepts with our data and trading clients. The technical priorities when developing our software were performance and scalability, and no other vendor to our knowledge was able to compete.”
Add to that the ease with which the q language allowed First Derivatives to provide rich functionality quickly for its clients, and the selection of kdb became even more obvious. “FD is a customer-centric company,” notes Brian. “Our decision to adopt a certain technology revolves around the benefits that it provides to our client base. We look for technologies that allow us to rapidly develop and deploy tailored solutions that are robust and scalable while allowing the flexibility to evolve to meet clients’ future business requirements.”
The core Kx engineering team worked closely with First Derivatives, and both groups continue to keep each other abreast of the company’s technology roadmaps and its clients’ priorities. “Our software development teams used kdb from Day One of the development of our data management and algo offerings,” continues Brian. “We re-engineered our FX trading platform to leverage kdb and q language capabilities and witnessed immediate results in terms of the throughput our execution engines were capable of handling. kdb also gave us the option of extending the post-trade analytics capabilities of the FX platform beyond the legacy technology.”
Today, FD continues to use kdb for high-volume feed processing, data management and analytics, execution engines, and risk applications, and looks forward to processing ever larger datasets in the future.
“Our ultimate reward,” says Brian, “has been the enduring satisfaction of our customers and their continuing eagerness to extend the use of our software.” read