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686K TPS with Spring Framework Web App and VoltDB

Tuesday, June 26, 2012

Written by Andrew Wilson


We’ve recently put up a series of blog posts describing the components of a Spring-MVC web application, including VoltDB as the database, that saves votes being called in for talent show contestants. Today I’ll talk about what happened when we benchmarked the Voter application on Amazon’s cloud platform. The short story – running on a suitable EC2 configuration (see details below), we achieved 686,000 TPS for a Spring-enabled application using VoltDB.

The Benchmark Application

I’ll start by summarizing the aforementioned blog posts, but you are welcome to read them: 

695k TPS with Node.js and VoltDB

Tuesday, April 17, 2012

Written by Henning Diedrich.


Hi, I’m Henning Diedrich, co-founder and CEO of Eonblast, Inc. I’m a guest contributor to VoltDB’s blog.


In February I was contacted by VoltDB about conducting a benchmarking project. The company had recently released an updated version of a Node.js client driver that had originally been authored by Jacob Wright, one of VoltDB’s community members.

877,000 TPS with Erlang and VoltDB

Friday, April 5, 2013

Written by Henning Diedrich

-Edited 5/2/13 by Henning Diedrich to correct configuration typos.

Running on a suitable EC2 configuration (see details below), with our new VoltDB Erlang driver we achieved 877,519 transactions per second.

I am Henning Diedrich[1], CEO of Eonblast Corporation[2] a games company. I would like to introduce the new Erlang VoltDB driver we created, a piece of software that allows two genre-defining technologies to work together: VoltDB[3] and Erlang[4].

The Driver

I first came to VoltDB on the hunt for a better database for heavy duty online-game servers.

Key Value Benchmark FAQ

Tuesday, June 1, 2010

What’s the point of this benchmark?

Point 1: Demonstrate SQL can be fast. Say what you want about our numbers and benchmark, but the language used to manipulate data was SQL and it clearly wasn’t bottlenecking VoltDB performance. We wanted to show the assumption that dropping SQL is a precondition for performance and scalability is false.


Point 2: VoltDB competes well on simple workloads like the key-value puts and gets, as well as complex workloads like our TPC-C like benchmark.

How can I verify what you did without code or details?

As of today, we’ve made the code used to run the benchmark and

Picture it: Three Nodes, Highly Available Cluster, ~1 Million Transactions/second – with VoltDB

Tuesday, June 4, 2013

You’ve probably heard about the VoltDB, the super fast distributed ACID SQL RDBMS for OLTP, but you might not be aware of its throughput capabilities in detail. VoltDB achieves its high throughput by eliminating the locking and latching of conventional databases. It’s also distributed and can automatically shard your data, and it has a bunch of other really cool features that make transaction processing a snap.


We took a key­-value application and implemented it in VoltDB (the app is available with the distribution if you want to try it). We set the app up on 4 Dell R510′s with 64GB and

Scaling with VoltDB: The Clustered Database

Wednesday, January 9, 2013

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 clustered

SGI/VoltDB Benchmark- More Details

Wednesday, October 13, 2010

Written by Tim Callaghan.


Yesterday’s press release documented a 30 node SGI Rackable Cluster running VoltDB achieving 3.4 million transactions per second (at 10ms latency) running the “Voter” application.


Impressive numbers, indeed. And the numbers are even more interesting when you understand the transactions. Each Voter transaction consists of: 2 selects 1 insert (table with an index) 2 updates (materialized views, each with an index) Therefore, the SGI Cluster was performing 17 million SQL statements per second!

VoltDB in-memory database achieves best-in-class results, running in the cloud, on the YCSB Benchmark

Wednesday, May 7, 2014

The development team at VoltDB recently ran VoltDB v4.2 against the Yahoo Cloud Serving Benchmark (YCSB), an industry-standard performance benchmark for cloud databases. We ran our test on as realistic a cluster setup as possible: commodity hardware that we could easily book as spot instances on EC2, with features like durability and high availability enabled. And we ran a varied mix of workloads with realistically sized, 1 KB rows, rather than focusing on a specific, overly favorable use case.

Why is VoltDB So Fast?

Thursday, January 13, 2011

First and foremost, VoltDB is focused on specific workloads. Most existing RDBMSs are designed to be general purpose, one-size-fits-all systems. Recently, there have been a lot of new databases introduced that achieve better performance by specializing in areas like analytics, graphs or streaming data. Few of these specialized systems focus on OLTP, and when they do, it’s often more about tuning, rather then a rethink. VoltDB was designed to be the most scalable transaction processing system out there, often making compromises unsuitable for other workloads.