Career Openings
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Volt Active Data 6.4 Passes Official Jepsen Testing
Key TakeawaysVolt Active Data hired Kyle Kingsbury (creator of Jepsen Tests) to validate their promise of strong serializability in their…
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The two types of databases: Defines the World, or Reacts to the World
Key TakeawaysDatabases either ‘Define the World’ (where actions must occur in the database to be real) or ‘React to the…
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The role of a fast database in the NFV revolution
Key TakeawaysInnovation in telecommunications has been primarily driven by hardware vendors, leading to vendor lock-in and slow progress.The telecom industry…
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From the Internet of People to the IoT and the Analytics of Things – industry examples
Key TakeawaysThe Internet of Things (IoT) has surpassed Big Data in the Hype Cycle and is expected to deliver significant…
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Do you have an IoT checklist?
Key TakeawaysConsumer IoT ideas should either be totally new or improve existing solutions significantly.For new IoT ideas, compelling financial incentives…
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A Question of Degree: Thoughts from the In-Memory Computing Summit
Volt Active Data was a sponsor of the recent In-Memory Computing Summit in San Francisco. I always enjoy going back…
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Introducing our new eBook, Architecting for the Internet of Things
Ryan Betts is one of Volt Active Data’s founding developers, and is currently our CTO. He’s been designing and building…
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Volt Active Data Cross Data Center Replication
Check out or documentation site to learn more about Volt Active Data Cross Data Center Replication. In section 11.3, you’ll…
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Continuous queries on streams in Volt Active Data using materialized views
Key TakeawaysVolt Active Data v6.6 introduces support for joins in materialized views, enhancing the ability to cache aggregate query results…
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New guides to help you on your Fast Data Journey
Key TakeawaysFast Data has reshaped industries and competition by changing how business value is created and captured.Evaluating business and technology…
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Accelerating Value for the Enterprise IoT
Key TakeawaysIIoT promises a new business paradigm with pervasive sensors measuring, monitoring, and analyzing data to improve productivity, operational efficiencies,…
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Call Center example: Integrating processing and state to make streaming problems simple to solve
Key TakeawaysThe article discusses the benefits of integrating processing, state, and transactions for solving stream processing problems, particularly in the…