Author: John Hugg

VoltDB 6.4 Passes Official Jepsen Testing

VoltDB hired Kyle Kingsbury, creator of the Jepsen Tests, to build a new, stronger, Jepsen test especially for VoltDB. We promise strong serializability in a distributed database, a stronger promise than almost any other system, and we’ve been working with Kingsbury to validate that promise. What is Jepsen Testing? From “Jepsen is an effort […]

Call Center example: Integrating processing and state to make streaming problems simple to solve

I recently gave a talk at the Strata + Hadoop World conference in San Jose on the benefits of integration of processing and state and transactions when solving stream processing problems. The talk described how a system like VoltDB makes the following things easier: Correlation and streaming joins Out-of-order message delivery Exactly-once processing semantics Precision accounting […]

Winning now and in the future: where VoltDB shines

2015 was a big year for VoltDB. Our product improved as we added exciting features and invested in making the product more robust. Our team has grown, as have the number of users, customers and revenue. However, three things stand out that really make 2015 for me. The kinds of customers we are attracting have […]

ACID: How to screw it up!

In my previous post, I described four applications (three implemented, one an example) that require, or at least strongly benefit from, strong ACID transactions. With that out of the way, we can now get to the fun bits. Today’s claim: most databases that claim to be 100% ACID compliant fudge definitions, goof up, or deliberately […]

Apps that need ACID

There’s a lot of discussion about the value of consistency and ACID transactions in data management. I thought it would be useful to describe three fully implemented enterprise-class applications, and one example application, that need ACID transactions. These descriptions should make an abstract concept a bit more concrete. “The Last Dollar Problem” Airpush is a […]

Fast Data Recipe: Design Data Pipelines

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 […]

Fast Data Recipe: Integrate Streaming Aggregations and Transactions

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 […]

Comparing Cloud Performance With YCSB

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 […]

Disambiguating ACID and CAP

The ACID properties and the CAP theorem are two important concepts in data management and distributed systems. It’s unfortunate that in both acronyms the “C” stands for “Consistency,” but actually means completely different things. What follows is a primer on the two concepts and an explanation of the differences between the two “C”s. What is […]

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