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451 Research Report “Points & Polygons: VoltDB adds Geospatial Support with v6.0”

Tuesday, February 16, 2016

Jason Stamper, lead analyst at 451 Research, reported today on VoltDB’s newest software release, v6.0. As Stamper points out, v6.0 builds on the foundation of VoltDB’s in-memory, massively parallel architecture. In today’s data-intensive world, your business is only as fast as your database.

 

We’re thrilled that 451 Research decided to highlight our newest release. We take great pains to understand market needs and deliver the tools to help you advance your enterprise to the next level of data management.

A Classification of Streaming Applications

Wednesday, April 13, 2016

The Internet of Things (IOT) is rapidly expanding the number of streaming applications as people sensor tag an increasing number of objects of significance. This adds to the historical streaming applications we have observed in financial services, the military, on-line gaming and elsewhere. In this blog post, we classify such streaming applications according to Table 1.

 

 

The vertical axis represents the latency requirements of the streaming application. The bottom row represents applications without severe requirements. In other words, multi-second response time is acceptable.

Be First to Value with a Mobile-aware Fast Data Strategy

Monday, April 4, 2016

It’s a land grab out there with new companies coming to market every day with cool new applications and services. These companies include consumer product and service innovators such as Uber, Airbnb, and Fitbit, as well as B2B leaders you may not know yet, such as VoltDB customers Emagine International and Openet. These companies are changing the way business value is created by capturing a massive mobile mind shift.

 

Mobile users are obsessed with their devices, tethered to them and check them 150 times a day.

Before & After - using VoltDB in Financial Services

Monday, March 14, 2016

Choosing a database is a complex affair. Is performance the most important factor in the decision? Is the selection constrained by incumbent infrastructure and applications? Or are you working on a new application and feel free to consider the newest, hottest technologies – but then you need to decide which to use?

 

Wading through available technologies and assessing not only listed features/benefits but also evaluating competing marketing claims can seem more arduous than building a DIY solution.

 

Additionally,  limiting your selection based on technology already being used or to the newest

Before & after: How fast data will enable the IoT

Wednesday, April 6, 2016

More than three billion people globally access the Internet via smartphones and other devices such as watches and fitness trackers. This number pales in comparison to the total number of connected devices and sensors in the Internet of Things (IoT) today. Industry analyst firm Gartner puts this figure at 6.4 billion, and projects growth to 20.8 billion devices by 2020, with nearly 5.5 million new things added to the IoT daily. It’s clear the economic value of the IoT lies with the connected machines, devices, and business and industrial systems that make up the sensor-driven IoT.

 

Data flows

Comparing Cloud Performance with YCSB

Tuesday, November 17, 2015

Introduction

Last year we published YCSB benchmarks that compared IBM SoftLayer with Amazon Web Services. This generated a lot of interest from lots of different folks in the cloud community. There was so much interest we decided to do it again with more platforms.

 

We reached out to an independent benchmarking enthusiast, Tim Callaghan from ACME Benchmarking, to run the tests for us. We compensated him for his time and work, but we took a hands-off approach to the actual benchmarking.

 

The nice thing about this kind of benchmarking is that we don’t care who wins.

Dealing with rapidly-growing tables

Wednesday, May 6, 2015

This post was contributed by guest blogger Dan Khasis

 

It’s no secret that the VoltDB NewSQL in-memory database is exceptionally good at high-speed transaction processing and complex decisioning. But,  in today’s highly specialized database ecosystem,  you shouldn’t use one database for everything just because you think you can.

 

You can certainly insert data at almost any velocity into VoltDB, but you will eventually run out of cluster memory (of course, you can solve this by adding nodes on the fly to increase cluster memory, although you may not need/want to store data in memory

Disrupters Use Fast Data to Create Advantage - So Can You

Tuesday, March 8, 2016

The overwhelming availability of fast data, the datafication of humanity, is igniting a new era of innovation and reshaping industries. Volumes of data are pouring into enterprises, drowning them in the details about their customers, their products, and their networks.

 

Market disrupters have figured out how to harness this inflow of data to create business value, the minute (or more precisely, the millisecond) it enters the enterprise.

Fast Data Enabler VoltDB in the 2015 Gartner Magic Quadrant

Friday, October 23, 2015

Gartner recently issued the 2015 Magic Quadrant for Operational Database management Systems and VoltDB is featured for the third year running!

 

VoltDB is the only in-memory SQL OLTP database in this Magic Quadrant report. It’s heartening to see all the hard work and dedication that has been put into building our company and product be recognized, but what I like best are the significant strengths called out:

  • Performance -- highest score for high-speed data ingestion
  • Fast Data -- more than half of VoltDB’s customers use our hybrid transactional/analytical processing (HTAP) capabilities to power

Fast Data Recipe: Design Data Pipelines

Monday, January 18, 2016

Processing big data effectively often requires multiple database engines, each specialized to a purpose. Databases that are very good at event-oriented real-time processing are likely not good at batch analytics against large volumes. Here’s a quick look at another of the Fast Data recipes from the ebook, “Fast Data: Smart and at Scale” Ryan Betts and I authored.

 

Data arriving at high-velocity, ingest-oriented systems needs to be processed and captured into volume-oriented systems.

Fast Data Recipe: Integrate Streaming Aggregations and Transactions

Thursday, January 7, 2016

In the VoltDB ebook, “Fast Data: Smart and at Scale,” Ryan Betts and I outline what we have found, through years of work and collective experience, to be tried-and-true design patterns and recipes for fast data.

 

High-speed transactional applications or operational applications that process a stream of incoming events are being built for use cases including real-time authorization, billing, usage, operational tuning, and intelligent alerting. Writing these applications requires combining streaming analytics with transaction processing on live data feeds.

 

Transactions in these applications

Fast Data: A look at a VoltDB Sample App

Thursday, November 13, 2014

In the age of Fast Data, being able to make decisions on a per-event basis is just as important as being able to handle the high ingestion rate. An example that demonstrates this concept well is clickstream processing.

 

Clickstreams record users’ activities on the web as they navigate through web pages. Events are either page requests to servers or browser events recorded on users’ computers. Clickstream analysis provides insights into users’ behaviors and preferences. The information is useful to applications for online advertising, social networks, security monitoring, marketing, etc.

 

How to Use Big Data to Acquire New Customers

Wednesday, June 3, 2015

This guest post was provided by Larisa Bedgood, Director of Marketing at VoltDB customer DataMentors. The post originally appeared on the Business 2 Community site, and is published here with permission.

 

Retailers know they need Big Data and are charging forward to get in the game. But many retailers continue to face challenges. What type of data should be collected? How should the data be used to generate insights? How do I measure ROI?

 

101data recently surveyed US retailers, across a range of sizes.

If You Think Big Data’s Challenges Are Tough Now…

Wednesday, January 28, 2015

This article was first published in The MIT Sloan Management Review on January 27, 2014. The author, Randy Bean, is CEO and managing partner of NewVantage Partners, a data and analytics executive management consulting and advisory firm. Click here to see the whole article.

 

…you should recognize that it’s only going to get tougher as data from sensors and smart devices becomes more prevalent.

 

According to the EMC/IDC Digital Universe Report, data is doubling in size every two years.

Introducing Fast Data: Smart and at Scale - VoltDB’s new ‘recipes’ eBook

Friday, September 11, 2015

Just in time for Strata + Hadoop NYC, Ryan Betts, VoltDB founding developer and CTO, and John Hugg, VoltDB founding developer have written a great eBook for O’Reilly Media - Fast Data: Smart and at Scale: Design Patterns and Recipes.

 

The question this book tries to answer for developers, enterprise architects and others is: How do you develop apps that combine real-time, streaming analytics with real-time decisions, using an architecture that's reliable, scalable, and simple?

Introducing VoltDB v6.0

Wednesday, January 27, 2016

VoltDB is already the go-to product for developing fast data applications because of its unparalleled performance, availability, and durability. v6.0 builds on that foundation by extending existing capabilities and simplifying the development process.

 

What does a VoltDB application look like? Some of the characteristics are:

  • Applications ingest and process lots of data - data (events) being delivered at hundreds of thousands to millions per second. The workloads being thrown at these applications are write-heavy.
  • Applications need to compute, track and display real-time analytics on live

Kinesis Rant

Friday, October 16, 2015

I am a firm believer in complexity budgets. Every feature adds complexity. Your product becomes less stable, less reliable, harder to test, and slower to develop as complexity increases. Our lives as software developers are, in large part, pitched battles against complexity. There is a hierarchy of preference when fighting complexity: zero-code is better than code; configuration is better than code; declarative is better than imperative; orthogonal is better than interwoven.

 

Amazon's Kinesis tutorial violates all of these rules. The tutorial sets forth a simple goal: count URL referrers.

Managing Fast Data in a Content Delivery Network

Monday, February 22, 2016

MaxCDN is a content delivery network (CDN) provider that emphasizes reducing the latency and increasing the reliability of its rich-content delivery. It provides CDN services to digital advertisers, ad networks, publishers, hosting providers, gaming companies, and mobile providers.

 

The company’s business challenge was to provide customers with real-time analytics of content delivery in addition to having a reliable and accurate billing engine.

My first (fast) 90 days

Friday, May 6, 2016

I changed jobs and companies a very fast 90 days ago, moving from a huge (I like to say that like Bernie Sanders says it, starting with a "Y" – I’m from New York after all) technology company to the much smaller VoltDB. In my previous role, I worked on data warehousing. The challenges we solved were about Big Data, but really mostly about Volume and Variety. Other parts of the company’s vast portfolio tried to address the Velocity part, but our group helped customers store massive amounts of data and scan it quickly. That was analytics.

New guides to help you on your Fast Data Journey

Tuesday, May 17, 2016

Fast Data has changed the way business value is created and captured, opening up a new era of competition and reshaping industries. But evaluating business and technology options for data is complex and rapidly evolving. For example, according to Gartner, through 2018, 90% of deployed data lakes will be useless, as they are overwhelmed with information assets captured for uncertain use cases. We posted an article recently all about "orphaned data". Deciding which areas to invest in, how those investments deliver value, and making good technology choices is mission critical for expanding your

On IoT day, a few thoughts about the future of data

Thursday, April 9, 2015

Today is the fifth Internet of Things (IoT) Day, a day that marks a significant change in how we work, how we control our homes, how we drive, how most everything is made and how most everything else in our lives is changing.  All this change is being driven by the tsunami of omnipresent data in our daily lives.

 

The Internet – a product of the 1960s-era ARPANET, in combination with Sir Tim Berners-Lee’s World Wide Web - has created the perfect storm for connectivity, providing the foundation off which the Internet of Things is exploding.

 

In little more than 40 years, we’ve gone from a world

Openet uses fast data to drive down TCO and support mobile data in real-time

Thursday, January 14, 2016

Openet, a leading independent supplier of real-time business support systems (BSS), ensures that more than 600 million mobile telecommunications users around the world enjoy the best network and data experience while enabling mobile operators to monetize data use in real-time.

 

In late 2012, Openet began evaluating potential replacements for its database infrastructure, primarily to drive down the TCO of its applications and solutions and to better support the real-time demands of mobile data.

 

They selected VoltDB.

 

VoltDB is able to provide a higher performance, in-memory database that could

The Datafication of humanity

Wednesday, August 12, 2015

The term “datafication” has typically referred to taking a process or activity that was previously invisible and turning it into data that can be tracked, monitored, and optimized. It was originally popular with the data modeling community but is experiencing newfound relevance with the accelerating technological advances we are experiencing, coupled with our abilities to capture many aspects of our world and our daily lives that have never been quantifiable before.

 

Datafication is no longer just about tracking and optimizing business processes; it is now integrating with real-world

The Fast Data Superpower

Monday, April 18, 2016

How many of us dreamed of having a superpower growing up? Be honest. I know for me it was flying. I bet everyone has a superpower they’d like to have.

 

At VoltDB we have a saying: make fast data work. We’ve put that into practice for all our clients, and they’ve developed some very cool, next gen applications that are disrupting their markets. For example, we helped Emagine International achieve a 253% increase in mobile offer purchases with their Real-time Event Decisioning (ERED) platform.

 

Emagine’s offering is a superpower for real-time personalization.

VoltDB partner deltaDNA brings hyper-personalization in on-line gaming

Monday, February 29, 2016

Many choices in computing and data processing are positioned as an either/or choice: either adopt Cloud or stick with physical data centers; either manage development via Agile or stay with waterfall processes; either use an RDBMS or a NoSQL database; either go all in to Big Data or try to extract value from data in real time with open source tools like Spark, or look for an enterprise-class solution with the stability, service and support required to manage a business.

 

Life is seldom so simple.

What We Can Learn from This Year’s Strata + Hadoop World Agenda

Friday, October 31, 2014

The recent Strata + Hadoop featured SQL, fast data, and streaming. The conference agenda of the premier Hadoop conference featured the word “Spark” more than 30 times. Throughout the conference, the importance of real-time, Fast Data processing dominated both hallway mindshare and the agenda.

 

Why?

 

At VoltDB we’ve been beating the drum (and providing the tools): the value of Big Data is found in real-time applications. Big Data exploration and analytics lead to new insights and new opportunity.

What's missing from IoT thinking: side effects

Thursday, March 31, 2016

IoT data management platforms must manage both data in motion (fast data) and data at rest (big data). As things generate information, the data needs to processed by applications. Those applications must combine patterns, thresholds, plans, metrics, and more from analytics run against collected (big) data with the current state and readings of the things (fast).  From this combination, they need to have some side effect.

 

That’s the part of IoT - and modern data management in general - that isn’t discussed enough: the side effects.

What’s in a fast data app development recipe?

Monday, September 14, 2015

In our book Fast Data: Smart and at Scale, we’ve demonstrated how to think about, and implement, software applications to solve the recurring problems a developer or architect working with fast streams of data encounters.

 

Fast Data applications are relatively new. Because they are new, the approach to solving them is still in flux. To that point, we have proposed a collection of patterns for common development challenges and complexities we see arise in our day-to-day work at VoltDB.

Why the Innovators of Data-Intensive Apps Use the Cloud

Thursday, February 11, 2016

I recently met with a bunch of VoltDB customers. These are companies in the business of data and developing the next generation of applications – they are at the forefront of an economy driven by data and the datafication of just about everything.

 

When I talked with these customers, I was struck by the fact that while they all operate in different industries and different geographies with very different products and services, they all have the same concerns.

 

They need to rapidly deploy services, realize time to value, and scale their IT infrastructures.

Worlds Apart? The Real-Time Data Disconnect

Wednesday, December 16, 2015

It may not be a surprise that business executives and their development teams don’t see eye-to-eye on everything. Especially when the challenge is tapping into a rapidly growing new technology trend like real-time data that can make your business smarter, faster, and more interactive. That is precisely what we found in one of the industry’s first surveys on the state of real-time data analysis in today’s enterprise, although there are important areas of agreement in addition to the disconnects.

 

The survey, conducted by Research Now and sponsored by VoltDB, examined how different roles within