Welcome!

Python Authors: AppDynamics Blog, Pat Romanski, Matt Davis, Donald Meyer, Liz McMillan

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
The platform combines the strengths of Singtel's extensive, intelligent network capabilities with Microsoft's cloud expertise to create a unique solution that sets new standards for IoT applications," said Mr Diomedes Kastanis, Head of IoT at Singtel. "Our solution provides speed, transparency and flexibility, paving the way for a more pervasive use of IoT to accelerate enterprises' digitalisation efforts. AI-powered intelligent connectivity over Microsoft Azure will be the fastest connected pat...
After years of investments and acquisitions, CloudBlue was created with the goal of building the world's only hyperscale digital platform with an increasingly infinite ecosystem and proven go-to-market services. The result? An unmatched platform that helps customers streamline cloud operations, save time and money, and revolutionize their businesses overnight. Today, the platform operates in more than 45 countries and powers more than 200 of the world's largest cloud marketplaces, managing mo...
Your applications have evolved, your computing needs are changing, and your servers have become more and more dense. But your data center hasn't changed so you can't get the benefits of cheaper, better, smaller, faster... until now. Colovore is Silicon Valley's premier provider of high-density colocation solutions that are a perfect fit for companies operating modern, high-performance hardware. No other Bay Area colo provider can match our density, operating efficiency, and ease of scalability.
CloudEXPO has been the M&A capital for Cloud companies for more than a decade with memorable acquisition news stories which came out of CloudEXPO expo floor. DevOpsSUMMIT New York faculty member Greg Bledsoe shared his views on IBM's Red Hat acquisition live from NASDAQ floor. Acquisition news was announced during CloudEXPO New York which took place November 12-13, 2019 in New York City.
At CloudEXPO Silicon Valley, June 24-26, 2019, Digital Transformation (DX) is a major focus with expanded DevOpsSUMMIT and FinTechEXPO programs within the DXWorldEXPO agenda. Successful transformation requires a laser focus on being data-driven and on using all the tools available that enable transformation if they plan to survive over the long term. A total of 88% of Fortune 500 companies from a generation ago are now out of business. Only 12% still survive. Similar percentages are found throug...
Atmosera delivers modern cloud services that maximize the advantages of cloud-based infrastructures. Offering private, hybrid, and public cloud solutions, Atmosera works closely with customers to engineer, deploy, and operate cloud architectures with advanced services that deliver strategic business outcomes. Atmosera's expertise simplifies the process of cloud transformation and our 20+ years of experience managing complex IT environments provides our customers with the confidence and trust tha...
The graph represents a network of 1,329 Twitter users whose recent tweets contained "#DevOps", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Thursday, 10 January 2019 at 23:50 UTC. The tweets in the network were tweeted over the 7-hour, 6-minute period from Thursday, 10 January 2019 at 16:29 UTC to Thursday, 10 January 2019 at 23:36 UTC. Additional tweets that were mentioned in this...
Today's workforce is trading their cubicles and corporate desktops in favor of an any-location, any-device work style. And as digital natives make up more and more of the modern workforce, the appetite for user-friendly, cloud-based services grows. The center of work is shifting to the user and to the cloud. But managing a proliferation of SaaS, web, and mobile apps running on any number of clouds and devices is unwieldy and increases security risks. Steve Wilson, Citrix Vice President of Cloud,...
Artificial intelligence, machine learning, neural networks. We're in the midst of a wave of excitement around AI such as hasn't been seen for a few decades. But those previous periods of inflated expectations led to troughs of disappointment. This time is (mostly) different. Applications of AI such as predictive analytics are already decreasing costs and improving reliability of industrial machinery. Pattern recognition can equal or exceed the ability of human experts in some domains. It's devel...
The term "digital transformation" (DX) is being used by everyone for just about any company initiative that involves technology, the web, ecommerce, software, or even customer experience. While the term has certainly turned into a buzzword with a lot of hype, the transition to a more connected, digital world is real and comes with real challenges. In his opening keynote, Four Essentials To Become DX Hero Status Now, Jonathan Hoppe, Co-Founder and CTO of Total Uptime Technologies, shared that ...