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 […]
451 Research Report “Points & Polygons: Volt Active Data adds Geospatial Support with v6.0”
Jason Stamper, lead analyst at 451 Research, reported today on Volt Active Data’s newest software release, v6.0. As Stamper points out, v6.0 builds on the foundation of Volt Active Data’s in-memory, massively parallel architecture. In today’s data-intensive world, your business is only as fast as your database. We’re thrilled that 451 Research decided to highlight […]
Why the Innovators of Data-Intensive Apps Use the Cloud
I recently met with a bunch of Volt Active Data customers. These are companies in the business of data and developing the next generation of applications – they are at the forefront of an economy driven by data and the datafication of just about everything. When I talked with these customers, I was struck by […]
Introducing Geospatial Capabilities in Volt Active Data v6.0
As part of our 6.0 release, we’ve added new data types and functions that let you work with geospatial data in your applications. If you care about where things are in the real world and how they relate to each other spatially, we have some new features that will help you out. The New Data […]
Introducing Volt Active Data v6.0
Volt Active Data 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 Volt Active Data application look like? Some of the characteristics are: Applications ingest and process lots of […]
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 […]
