For growth initiatives, many companies are looking to innovate by ramping analytical, mobile, social, big data, and cloud initiatives. For example, GE is one growth-oriented company and just announced heavy investment in the Industrial Internet with GoPivotal. One area of concern to many well-established businesses is what to do with their mainframe powered applications. Mainframes are expensive to run, but the applications that run off of them are typically very important and the business can not afford to risk downtime or any degradation in service. So, until now the idea of modernizing a mainframe application has often faced major roadblocks.
There are ways to preserve the mainframe and improve application performance, reliability and even usability. As one of the world’s largest banks sees, big, fast data grids can provide an incremental approach to mainframe modernization and reduce risk, lower operational costs, increase data processing performance, and provide innovative analytics capabilities for the business—all based on the same types of cloud computing technologies that power internet powerhouses and financial trading markets. Continue reading →
Just like we saw in the dot-com boom of the 90s and the web 2.0 boom of the 2000s, the big data trend will also lead companies to make some really bad assumptions and decisions.
Hadoop is certainly one major area of investment for companies to use to solve big data needs. Companies like Facebook that have famously dealt well with large data volumes have publicly touted their successes with Hadoop, so its natural that companies approaching big data first look to the successes of others. A really smart MIT computer science grad once told me, “when all you have is a hammer, everything looks like a nail.” This functional fixedness is the cognitive bias to avoid with the hype surrounding Hadoop. Hadoop is a multi-dimensional solution that can be deployed and used in different way. Let’s look at some of the most common pre-concieved notions about Hadoop and big data that companies should know before committing to a Hadoop project: Continue reading →
The world’s largest banks have historically relied on mainframes to manage all their transactions and the related cash and profit. In mainframe terms, hundreds of thousands of MIPS are used to keep the mainframe running these transactions, and the cost per MIP can make mainframes extremely expensive to operate. For example, Sears was seeing the overall cost per MIP at $3000-$7000 per year and didn’t see that as a cost-effective way to compete with Amazon. While the price of MIPS has continued to improve, mainframes can also face pure capacity issues.
In today’s world of financial regulations, risk, and compliance, the entire history of all transactions must be captured, stored, and available to report on or search both immediately and over time. This way, banks can meet audit requirements and allow for scenarios like a customer service call that results in an agent search for the transaction history leading up to a customer’s current account balance. The volume of information created across checking, savings, credit card, insurance, and other financial products is tremendous—it’s large enough to bring a mainframe to its knees. Continue reading →
The new database is opening up significant career opportunities for data modelers, admins, architects, and data scientists. In parallel, it’s transforming how businesses use data. It’s also making the traditional RDBMS look like a T-REX.
Our web-centric, social media, and internet-of-things are acting as a sea-change to break traditional data design and management approaches. Data is coming in at increasing speeds, and 80% of it cannot be easily organized into the neat little rows and columns associated with the traditional RDBMS.
Mobile Location Based Services are on the rise. After several false starts back in the mid 2000s, every mobile user now depends on their phones to tell them where they are, where their friends are, and to engage with social media like Facebook and Foursquare. A report by Juniper Research suggests this market is expected to breach over $12 billion next year, where it hardly existed a few years ago at all.
This is in part because mobile apps have become ubiquitous now. In order to remain relevant, businesses need to interact socially and have a web store to remain accessible to their wandering customers.
Building a geographically aware application from scratch sounds daunting and like a lot of initial data setup. It doesn’t have to be. Products like vFabric Postgres (vPostgres) can be used along with the PostGIS extensions to perform geographic-style queries. Then, public data and an open source visualizer can be used to transform the query into a meaningful result for your application or end user.
Ensuring your systems run smooth even when your data center has a hiccup, or a real disaster strikes is critical for many companies to survive when hardships befall them. As we enter the age of the zettabyte, seamless disaster recovery has become even more critical and difficult. There is more data than we have ever handled before, and most of it is very, very big.
Most disaster recovery (DR) sites are in standby mode—assets sitting idle, waiting for their turn. The sites are either holding data copied through a storage area network (SAN) or using other data replication mechanisms to propagate information from a live site to a standby site. When disaster strikes clients are redirected to the standby site where they’re greeted with a polite “please wait” while the site spins up.
At best, the DR site is a hot standby that is ready to go on short notice. DNS redirects clients to the DR site and they’re good to go.
What about all the machines at the DR site? With active/passive replication you can probably do queries on the slave site, but what if you want to make full use of all of that expensive gear and go active/active? The challenge is in the data replication technology. Most current data replication architectures are one-way If it’s not one-way, it can come with restrictions—for example, you need to avoid opening files with exclusive access. Continue reading →
When you are a software company like VMware, you are tied to the success of your partners in the field standing shoulder to shoulder with your customers, guiding them to a successful deployment. Their success and growth directly reflects your customer’s success as your own success in the marketplace.
Partners are focused on solutions that customers care about because it is the only way to stay in business and grow. Today, 10 representatives from technology consulting organizations share their perspectives on how they are using the VMware vFabric Suite to achieve success with customers. Each includes a video or you can visit the full vFabric playlist on VMwareTV.
1. Modernizing Legacy Apps to Cloud and SaaS with vFabric
“In vFabric we see a very attractive modern cloud application platform. So while spring and vFabric represent very attractive alternatives for new application development, what we see with our clients are is the desire to modernize and transform existing applications to take advantage of those same benefits of vFabric. The run time benefits, the design time benefits.”—Chase Crawson, Director of Application Services, CSC Continue reading →
Day 2 of the O’Reilly Strata Conference is starting here in Santa Clara, California and the focus is very much on data. In 2005, Tim O’Reilly predicted: “Data is the Next Intel Inside.” At VMware, big, fast data has never been so critical for our customers and innovations are transforming the cloud applications landscape at an unprecedented rate. This conference comes at the perfect time to reset what everyone knows about big, fast data.
The conference kicked off yesterday with several brief 20 minute keynotes. They were all succinct and to the point. Greenplum‘s Scott Yara reflected on how the big data market has grown tremendously over the past few years and mentioned several key data scientist practitioners. Scott also mentioned the increased investment in open source Hadoop. Of course, Strata comes on the heels of the Greenplum Pivotal HD announcement on Monday which launched their distribution of Hadoop which can improve performance 50X to 500X when compared to existing SQL-like services on top of Hadoop.
Another great keynote presentation was from Yael Garten, a Senior Data Scientist from LinkedIn. Yael leads the mobile data analytics team. She began by polling the audience and noting that many in the audience had already been on 3 different devices that morning and it wasn’t even 9:30 am yet. She noted we’re constantly connected, and we need to use data to personalize the experience for users no matter what device we’re on. She had an interesting graph highlighting device use and laptop use during our morning time of “coffee to couch”. And those uses are different in the US compared to places like India. Continue reading →
If you aren’t familiar with Strata, it is a great conference for those building apps in the cloud. Its focus is all about the future of big data and how to use big data successfully. Speakers include representatives from Google, VMware, Amazon, Microsoft, and many other software companies focused in the big data space. Topics include: Continue reading →
According to one of our partners, vFabric SQLFire is a product he wishes more customers would use.
“SQLFire is a game-changer. I think many companies underestimate the value of scaling the data later horizontally. Every project I propose has a business case, and I see a tremendous amount of value being unlocked with this product—not just for the CIO or CTO’s agenda, but for the CFO and CEO. Then, you add the fact that the whole application stack is virtualized and has solid integrations. It’s a simple story, the product allows you to add a lot of value in a really cost effective way.”
What makes SQLFire such a game-changer?
In this article, we’ll talk more about three game-changing capabilities: server groups, partitioning, and redundancy.
If you haven’t been following our stories on SQLFire, see the end of this article for a list of posts and key capabilities that help explain how transformative SQLFire can be to your data management strategies. Continue reading →