My last few posts have discussed parts of a web application that integrate VoltDB into a Spring web application. Today I will show how all the pieces are put together to build a low latency, high throughput Spring-MVC application. Much of my focus will be on the data layer where VoltDB resides, but I will go all the way up to the browser too.

The application is simple. It has two main parts. The first is a scheduled process that casts votes into VoltDB. Those votes simulate people calling in and voting for their favorite contestant in a talent show. … Read more

Mapping one type to another is a pretty common task. Hibernate and other ORM’s map a result from a data source’s native representation to an application specific representation. In English, I want to convert a JDBC result set, or data objects, into a collection of POJOs (plain old Java objects) using some kind of data mapping tool or API. Spring exposes a low level service provider interface that makes it very easy to convert one data type to another with either built-in converters or customer converters, allowing a developer to support just about any conversion one can think of. Today … Read more

This is the second post in a two-part series entitled The Big Data Value Continuum.  You can find Part 1 here.

Recall that in the world of Big Data, our fundamental assumption is that data no longer resides in a static database for its entire life.  Big data demands that we squeak out the most value from the data that we have at every stage of its lifecycle.  And, oh yeah, we’re collecting way more today than we did yesterday, so get ready for that challenge, too.

Part 2: Putting the Pieces Together

Let’s build on the concepts we … Read more

In a previous life I had a requirement that a web application scanned the expiration date of purchased content and sent one of three emails letting the user know that the item would expire soon, was going to expire very soon and that the item has expired. It fired up at early in the morning when the server had the lowest utilization. Later, I had to write a similar feature that would run every couple of minutes. It wasn’t terribly hard to implement the logic, but the scheduler was an external component that required much more work to configure than … Read more

The purpose of this blog posting is to discuss strategies for handling decision support queries in Online Transaction Processing (OLTP) applications.  First, I want to talk about the two classes of OLTP applications that I see in the marketplace.

The first is the traditional OLTP market that has been present for years, and is typified by purchasing Wall Street stocks.  A collection of humans (stock brokers or end-users over the web) interact with an OLTP system to trade securities.  The brokerage house (and end users for that matter) also want to run decision support queries to learn about historical trends … Read more

This is the first post in a two-part series entitled The Big Data Value Continuum.  You can find Part 2 here.

Technology markets are challenging enough to understand but, when you throw in the added noise that typically accompanies early markets, gaining real insights can be next to impossible.  It is not unusual to have ten or more vendors in a particular segment and adjacent segments, and countless products attempting to solve similar customer problems. Needless to say, tech markets are rarely clear in the beginning.

Big Data is just such a market today. One of the challenges we … Read more

Last week I gave a webinar entitled OldSQL vs. NoSQL vs. NewSQL for New OLTP.  If you missed the live webinar and want to view the recorded version, you’ll find it here (you may need to scroll down to find it).  Below is a list of questions that live webinar attendees asked, in no particular order.  If you have follow-on questions, reply to this post and I or someone else from VoltDB will answer them.

Webinar Questions and Answers

1.  Does VoltDB run on Scale up NUMA like systems or is it designed primarily to run on scale out clusters?… Read more

This is the first in a series of blog posts in which I will explore various aspects of On-Line Transaction Processing (OLTP).   In this post, I’ll examine main memory storage as an alternative to disk for traditional and “New OLTP” systems.

Traditional relational DBMSs, Hadoop and most of the NoSQL offerings store their data on disk.  In contrast, VoltDB is a main memory DBMS.

First, it should be noted that main memory is getting very cheap.  It is straightforward to put 50 Gbytes of memory on a $5,000 server.  Beefy servers these days have 10 times that amount. Moreover, many … Read more