Database Vendor Versant Eyes HPC Market

By John West

September 29, 2009

Object database maker Versant has done pretty well in its market niche, with a list of 1,500 customers that includes well-known names like AT&T, Alcatel-Lucent, Ericsson, and British Airways. With 80 people, a market cap of $65 million USD, and revenue last year of $25 million, Versant is a small company by most any measure. But it is in a small industry: while the relational database business is valued around $10 billion a year these days, the object database market is on the order of only a couple hundred million dollars a year.

A niche product for a niche market, Versant’s core technology isn’t needed everywhere, but it is indispensable where it is needed. And the company is hoping to demonstrate that at least some HPC users need it.

Alright, first things first: what’s an object database? Object databases provide persistent storage for, well, objects. Imagine you have a backpack object, and that backpack has a flashlight object and a rope object in it. When you retrieve the backpack object out of the database you get the flashlight and the rope along with it, no extra queries required (well, actually you probably get pointers to those objects, but that’s a detail).

With a relational database, data is stored in rows and columns in (probably many) tables in your database. In our backpack example all backpacks may be listed in a specific table, with each given a unique ID. Another table may store the various camp tools, like ropes and flashlights, that campers may put in backpacks. And yet a third table would put these together, with one row holding the ID for our backpack and the flashlight, and another row holding the ID for our backpack again and the rope.

The mechanics of retrieval offer an important distinction with the relational model: unlike a relational database wherein programmers have to structure a database request (query) in a separate language called SQL, an object database works in the context of a regular programming language such as C++, C or Java. So, for the object database, a programmer calls the backpack object into memory and it comes along with (pointers to) the flashlight and rope objects. But a programmer using a relational database would constructuct a SQL query that first pulled all of the records from the third table to find all the entries that are associated with our backpack’s ID. Then he’d have to construct other queries to look in the camp tool tables to find out what kinds of tools were attached to those IDs.

Despite the apparent added headaches of working with SQL and a relational database, they can be very (very) fast in a wide variety of applications, and have been proven to scale to enormous sizes. They are ubiquitous in nearly every enterprise, and you probably have a bunch in your own HPC center for managing inventory, user tickets, and so on. On the other hand, there are well-documented situations in which object databases are not only easier for a developer to deal with, they are much faster than the alternatives.

“Complexity and concurrency are the two things that we look for in application profiles that would lend themselves well to an object-oriented database,” says David Ingersoll, Versant’s VP of sales (Americas and APAC).

Of course, in traditional high performance technical computing, the choices aren’t between relational and object databases. The choices are between using any kind of database at all and flat files. And Ingersoll acknowledges this is a key obstacle they face in talking with clients, “One challenge is just to get people to realize that they need a database and not just a filesystem.”

But he isn’t coming to HPC empty-handed. When he briefed us about Versant’s potential in the HPC space, Ingersoll talked about examples of traditional HPC users using Versant’s object databases in HPC applications today; particularly, applications with large streaming data. For example, the Air Force Weather Agency uses a Versant database to store real-time satellite imagery that is then fed into computational models for cloud forecasts. Other similar applications include the European Space Agency’s Herschel Space Observatory, where Versant is the mission database, and Verizon, where real-time call data are streamed into a hierarchical set of databases that are used for near real-time fraud detection.

Exxon Mobil is also using Versant’s technology in its reservoir simulation system, EMPower. In its application, results from large-scale numerical simulations are stored in the database and then subjected to analytics routines that answer questions about where to place wells, when and where to inject fluids, and so forth.

In many of their HPC examples, Versant’s users are storing the data in a large database that itself may be hosted on a cluster. Hundreds or thousands of clients then access the database from the compute nodes of other clusters to process the data and answer mission questions. This is a basic level of parallelism supported by Versant, which also offers multi-threaded and parallel queries baked into the database engine along with a dual cache and object-locking for high concurrency support.

Object databases themselves aren’t new: work started on them in the 1980s and spiked in the early 1990s when all the cool kids were drinking the O-O Kool-Aid. As object-oriented languages have become mainstream (including C++, Java, and C#), programmers have struggled with mapping their languages to relational databases because they wanted to work with what they knew: familiar languages and familiar (relational) databases.

And this points to a key challenge in positioning an object database technology for HPC: if you aren’t using an object-oriented language, you aren’t going to see much benefit. “C and FORTRAN don’t lend themselves well [to object databases] because the domain models are very flat, very procedurally oriented, and they’re not going to have a lot of inter-relationships,” says Ingersoll. “At that point, the benefit of our system really falls down.”

Versant is targeting markets and applications where C++ and Java are already in use for intensive computing, or where the practictioners don’t have a vast store of legacy code in their toolboxes already. Areas like bioinformatics offer a lot of potential, not only because of the very modern nature of many of those codes, but also because the domain data model is inherently object-oriented. According to Ingersoll, “We are at that point where people are just coming [into HPC in these domains], so if we can get in front of that wave then that’s a benefit for us.”

Versant is looking to build partnerships as it tries to wriggle into the HPC market. Ingersoll let us know that they are talking to both Penguin Computing and Panasas about working more closely together. The Panasas opportunity seems particularly appropos given the object-based nature of Panasas’ PanFS file system. In fact, according to Ingersoll, Versant is already being used in the financial services industry on a cluster outfitted with Panasas storage.

Versant doesn’t have the object database market to itself, of course. It competes with companies like Objectivity and Intersystems in the object database market, and with Microsoft and Oracle, both of which have a growing interest in the technology. Object databases are an interesting technology, and in twenty years of development Versant has structured a robust solution. But getting databases into HPC, even into the developing segments of our community, will be a tall order. Differentiating object databases from relational databases to HPC people layers another challenge on top of that.

This is a challenge that Ingersoll feels Versant is equal to, “We are getting the market to understand that difference,” he says. “If people are investigating what steps to take today, we have a much better shot at educating them than if they are going to be moving that application from C to C++, and you’re really going to be thoughtful about how you’re modeling the application, then we provide orders of magnitude of performance benefits.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Scalable Informatics Ceases Operations

March 23, 2017

On the same day we reported on the uncertain future for HPC compiler company PathScale, we are sad to learn that another HPC vendor, Scalable Informatics, is closing its doors. Read more…

By Tiffany Trader

‘Strategies in Biomedical Data Science’ Advances IT-Research Synergies

March 23, 2017

“Strategies in Biomedical Data Science: Driving Force for Innovation” by Jay A. Etchings is both an introductory text and a field guide for anyone working with biomedical data. Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Google Launches New Machine Learning Journal

March 22, 2017

On Monday, Google announced plans to launch a new peer review journal and “ecosystem” Read more…

By John Russell

HPE Extreme Performance Solutions

HFT Firms Turn to Co-Location to Gain Competitive Advantage

High-frequency trading (HFT) is a high-speed, high-stakes world where every millisecond matters. Finding ways to execute trades faster than the competition translates directly to greater revenue for firms, brokerages, and exchanges. Read more…

Swiss Researchers Peer Inside Chips with Improved X-Ray Imaging

March 22, 2017

Peering inside semiconductor chips using x-ray imaging isn’t new, but the technique hasn’t been especially good or easy to accomplish. Read more…

By John Russell

LANL Simulation Shows Massive Black Holes Break ‘Speed Limit’

March 21, 2017

A new computer simulation based on codes developed at Los Alamos National Laboratory (LANL) is shedding light on how supermassive black holes could have formed in the early universe contrary to most prior models which impose a limit on how fast these massive ‘objects’ can form. Read more…

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Intel Ships Drives Based on 3D XPoint Non-volatile Memory

March 20, 2017

Intel Corp. has begun shipping new storage drives based on its 3D XPoint non-volatile memory technology as it targets data-driven workloads. Intel’s new Optane solid-state drives, designated P4800X, seek to combine the attributes of memory and storage in the same device. Read more…

By George Leopold

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

New Japanese Supercomputing Project Targets Exascale

March 14, 2017

Another Japanese supercomputing project was revealed this week, this one from emerging supercomputer maker, ExaScaler Inc., and Keio University. The partners are working on an original supercomputer design with exascale aspirations. Read more…

By Tiffany Trader

Nvidia Debuts HGX-1 for Cloud; Announces Fujitsu AI Deal

March 9, 2017

On Monday Nvidia announced a major deal with Fujitsu to help build an AI supercomputer for RIKEN using 24 DGX-1 servers. Read more…

By John Russell

HPC4Mfg Advances State-of-the-Art for American Manufacturing

March 9, 2017

Last Friday (March 3, 2017), the High Performance Computing for Manufacturing (HPC4Mfg) program held an industry engagement day workshop in San Diego, bringing together members of the US manufacturing community, national laboratories and universities to discuss the role of high-performance computing as an innovation engine for American manufacturing. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Leading Solution Providers

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This