Welcome!

Perl Authors: AppDynamics Blog, Liz McMillan, Mike Hicks, RealWire News Distribution, Bob Gourley

Related Topics: Java IoT, Microsoft Cloud, Perl, Python

Java IoT: Article

Big Data Kills 30-Year-Old Market

Applications need to go to “Big Data,” not the other way around

Data Services Journal

If you’ve got simply scads of data – and why wouldn’t you? – it’s doubling every 18 months – and are shuttling it to an application for analysis, you’re doing it wrong.

That’s so…so, well, 1980.

According to Aster Data, applications need to go to “Big Data,” not the other way around.

And to do that the company’s got a massively parallel data-application server that can embed applications inside a massively scalable MPP data warehouse and analyze petabytes of data – or terabytes, if that’s all you’ve got – ultra-fast.

Apps are automatically parallelized for scale; users can take their existing Java, C, C++, C#, .NET, Perl and Python applications, MapReduce-enable them and push them down into the data.

The widgetry runs on a cluster of commodity boxes. Figure five servers to start although parallelized applications can utilize terabytes of memory and thousands of CPU cores.

This is not the data warehouses, DBMSes and data analytics solutions of the last three decades that have separated data from applications, a technique Aster says results in massive data movement, latency and restricted analysis.

Traditional systems weren’t built to process billions of rows of data in seconds or handle chi-chi stuff like real-time fraud detection, customer behavior modeling, merchandising optimization, affinity marketing, trending and simulations, trading surveillance and customer calling patterns.

They were built for data sampling, an inexact science. They simply fail in today’s big data, analytics-intensive environments, Aster says.

The company’s Aster Data 4.0 brings data and applications together in one system, fully parallelizing both, to deliver ultra-fast analysis on massive data scales. And it’s got customers like comScore, Full Tilt Poker, Telefonica I+D, SAS and MySpace, with the big clutch of data of all, saying it’s right.

Aster’s Massively Parallel Data-Application Server 4.0, based on research done at Stanford University before commercialization started a couple of years ago, lets companies embed application logic in Aster’s MPP database, which includes MapReduce. It was Aster that brought MapReduce to SQL, a trick it’s now building on.

In Aster’s system data management lives independent of the application processing but – and this is important – the data and applications execute as first-class citizens, with their own respective data and application management services.

The Data-Application Server is responsible for managing and coordinating the cluster’s activities and resource sharing. It acts as a host for the application processing and the data managed inside the cluster.

As a data host, it manages incremental scaling, fault tolerance and heterogeneous hardware for application processing and it manages workloads via Aster’s new Dynamic Workload Management (WLM) capability.

Aster says WLM, described as the first dynamic workload management capability available on a MPP system to run on commodity hardware, can support hundreds of concurrent mixed workloads. It manages data storage, transactional correctness, online backups and information lifecycles (ILM).

The separation of data management and application processing is supposed to provide maximum application portability so a wide range of applications can be pushed down into the system.

Aster says this data analysis architecture distinguishes its solution from lightweight implementations of MapReduce, including what some vendors refer to as ‘In-Database MapReduce.

Richard Zwicky, president of Enquisite, the company that provides search optimization software and solutions, says that with Aster Data, response times for large queries has dropped from five minutes to five-10 seconds, and queries that previously weren’t possible now can be executed in 20-30 seconds.

Aster Data is backed by Sequoia Capital, Jafco Ventures, IVP and Cambrian Ventures, as well as Google’s first investor David Cheriton, Ron Conway and Rajeev Motwani.

More Stories By Maureen O'Gara

Maureen O'Gara the most read technology reporter for the past 20 years, is the Cloud Computing and Virtualization News Desk editor of SYS-CON Media. She is the publisher of famous "Billygrams" and the editor-in-chief of "Client/Server News" for more than a decade. One of the most respected technology reporters in the business, Maureen can be reached by email at maureen(at)sys-con.com or paperboy(at)g2news.com, and by phone at 516 759-7025. Twitter: @MaureenOGara

Comments (1)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


IoT & Smart Cities Stories
Dion Hinchcliffe is an internationally recognized digital expert, bestselling book author, frequent keynote speaker, analyst, futurist, and transformation expert based in Washington, DC. He is currently Chief Strategy Officer at the industry-leading digital strategy and online community solutions firm, 7Summits.
Digital Transformation is much more than a buzzword. The radical shift to digital mechanisms for almost every process is evident across all industries and verticals. This is often especially true in financial services, where the legacy environment is many times unable to keep up with the rapidly shifting demands of the consumer. The constant pressure to provide complete, omnichannel delivery of customer-facing solutions to meet both regulatory and customer demands is putting enormous pressure on...
IoT is rapidly becoming mainstream as more and more investments are made into the platforms and technology. As this movement continues to expand and gain momentum it creates a massive wall of noise that can be difficult to sift through. Unfortunately, this inevitably makes IoT less approachable for people to get started with and can hamper efforts to integrate this key technology into your own portfolio. There are so many connected products already in place today with many hundreds more on the h...
The standardization of container runtimes and images has sparked the creation of an almost overwhelming number of new open source projects that build on and otherwise work with these specifications. Of course, there's Kubernetes, which orchestrates and manages collections of containers. It was one of the first and best-known examples of projects that make containers truly useful for production use. However, more recently, the container ecosystem has truly exploded. A service mesh like Istio addr...
Digital Transformation: Preparing Cloud & IoT Security for the Age of Artificial Intelligence. As automation and artificial intelligence (AI) power solution development and delivery, many businesses need to build backend cloud capabilities. Well-poised organizations, marketing smart devices with AI and BlockChain capabilities prepare to refine compliance and regulatory capabilities in 2018. Volumes of health, financial, technical and privacy data, along with tightening compliance requirements by...
Charles Araujo is an industry analyst, internationally recognized authority on the Digital Enterprise and author of The Quantum Age of IT: Why Everything You Know About IT is About to Change. As Principal Analyst with Intellyx, he writes, speaks and advises organizations on how to navigate through this time of disruption. He is also the founder of The Institute for Digital Transformation and a sought after keynote speaker. He has been a regular contributor to both InformationWeek and CIO Insight...
Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
To Really Work for Enterprises, MultiCloud Adoption Requires Far Better and Inclusive Cloud Monitoring and Cost Management … But How? Overwhelmingly, even as enterprises have adopted cloud computing and are expanding to multi-cloud computing, IT leaders remain concerned about how to monitor, manage and control costs across hybrid and multi-cloud deployments. It’s clear that traditional IT monitoring and management approaches, designed after all for on-premises data centers, are falling short in ...
In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...