VoltDB 3.0 introduces the use of JSON-encoded columns to allow more flexibility in how you structure and interact with your data. New SQL functions and index capabilities let you work more naturally with JSON data while maintaining the efficiency and transactional consistency of a relational database.

How?  A VoltDB JSON Example

Let’s assume that you want to implement a single sign-on (SSO) application using VoltDB.  You wish to store the login session for a set of different online sites under a common username.  Each login session could hold different user state, simple data values or possibly more complex structures. Additionally, … Read more

Register nowto join us via live streaming!

Can’t make it to Santa Clara tonight? That doesn’t mean you can’t attend Stonebraker Live!

Join us via live stream at 6:30 p.m. Pacific to hear from database legend Mike Stonebraker, as well as VoltDB’s VP of Market Strategy, Mark Hydar, and Co-founder, Scott Jarr.… Read more

This is part 2 (of 2) of my Programming VoltDB – Easy, Flexible and Ultra-fast series. Blog post, part 1, showed how to build a VoltDB application using ad hoc queries and achieving thousands of transactions a second. It also showed how converting that logic to use VoltDB stored procedures allowed you to parallelize query execution and achieve 100,000+ transactions a second on a single node. In this blog post I’ll talk about scaling beyond 100,000 transactions per second by creating a VoltDB clustered database.

There are primarily two reasons why you would want to run VoltDB as a … Read more

John Hugg was talking with me today about a way to reduce the complexity of error checking in a stored procedure and how rarely it is used. VoltDB’s stored procedures let you set “expectations” on each SQL statement. Those expectations can eliminate several lines of code leading to shorter, readable and more reliable stored procedures.

Consider the following sample:

Example.DDL

LoginProc1.java

LoginProc2.java

LoginProc1 checks for a row count and returns either a 0 or a 1 if the username and password combination could not be found. LoginProc2 sets an expectation that the results of voltExecuteSQL() will return exactly one … Read more

Upserts in VoltDB

The idea behind an upsert is that you try an update or an insert query first and if it fails, you then do the other query.
Why do an upsert? Upserts tend to be very fast in traditional databases because they can execute in as little as one query or as many as two. Consequently, a good upsert strategy has only two defined queries (insert and update) rather than three (insert, update and select). More importantly, “upsert” itself can be a keyword in which the database understands that it is responsible for figuring out whether to update … Read more

A while ago I published my Go VoltDB driver to github (https://github.com/rbetts/voltdbgo).  I wrote the driver for three reasons: to learn and write a little go; to be able to test and script against VoltDB using go; and to experiment with some different VoltDB client patterns.

We, and the community, have written several production quality drivers for VoltDB (available at http://www.voltdb.com/community/downloads.php). The go driver, however, has not been tested for production use.

With caveats complete, what’s up with voltdbgo?

Firstly, it only supports synchronous clients. VoltDB 3.0 has greatly improved response latency for synchronous interactions and the … Read more

My name is Xin Jia and I was one of the student interns at VoltDB this summer. For one of my projects, I worked on a feature that greatly improved the performance of ranking-related queries.

Finding the rank of an entry in a sorted list of data is a common operation in a lot of applications. Take a leaderboard within gaming application as an example: it is common to have a scoreboard that keeps track of users’ scores. Questions like, “what are the top-n users and their corresponding scores?”, or “what is the rank of a certain user?” are … Read more

NewSQL and NoSQL databases present developers with a new and interesting programming model where there are fewer connections to the database, query parallelism, partitions and an easy model for supporting new clusters. Last month I presented a webinar introducing the basics of application development using VoltDB. We had a lot of great questions and I thought it would be handy to write them up and share the answers with everyone.

Q: Can you address how you would handle joining tables that have different partition keys?  Would you not partition the tables in that case?
A:  For multi-partition queries you join … Read more

Announcing VoltDB v3.0 – Preview Release

The next major release of VoltDB, version 3.0, is right around the corner.  In anticipation of this release, we’re announcing a preview release of the v3.0 offering, available immediately.  A brief overview and details on how you can preview this exciting release is found below.
What is VoltDB v3.0?

The VoltDB v3.0 release includes a set of user-visible features, including new SQL (specifically column functions), ad hoc SQL execution performance, Export enhancements, online schema changes, and a more streamlined application development process.  Under the covers, however, VoltDB v3.0 includes a new transaction coordination architecture … Read more

Making an Impact: VoltDB Engineering Interns

Summer went by too fast in New England!  We are already missing our two engineering internship students, Xin Jia from Brown University and Zheng li from University of Massachusetts, Lowell.

During their internship, Xin and Zheng worked on numerous projects, explored new ideas, and helped accelerate the launch of product features. In short, they were big contributors to VoltDB.  Some of their projects have already released in VoltDB 2.8.1. Xin worked on implementing several SQL functions as well as implementing counting index functionality to support efficient and fast rank related queries (look for his … Read more