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fast data

Comparing Cloud Performance with YCSB

Tuesday, November 17, 2015


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

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.

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

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.




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 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.

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