Category: Volt Capabilities
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3 min read
NewSQL in Plain English
Read more: NewSQL in Plain EnglishEditor’s note: This post is re-posted here by permission from the author. The original post was on LinkedIn on January 10, 2018. The world has changed massively in the past 20 years. Back in the year 2000, a few million users connected to the…
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QuickStart Video: Using Volt Active Data With Docker
Read more: QuickStart Video: Using Volt Active Data With DockerDocker is a powerful tool that many of our customers and community members use for the development and testing of distributed systems. What You’ll Learn in This Video Recently, our Customer Success Manager, Ben Ballard, presented a Quick Start Tutorial on this…
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Database Resolutions for 2018
Read more: Database Resolutions for 2018The New Year brings about the perfect time to start fresh and set some new goals. So, in the spirit of things, we’ve laid out a few New Year’s resolutions that all database professionals can take into account as they look to…
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“Forrester Wave Translytical Data Platforms Q4 2017” Puts a Good Foot Forward But Doesn’t Take Users Far Enough on the Selection Criteria
Read more: “Forrester Wave Translytical Data Platforms Q4 2017” Puts a Good Foot Forward But Doesn’t Take Users Far Enough on the Selection CriteriaForrester recently published a new Wave™ report on Translytical Data Platforms. In it, they define a Translytical Data Platform as: “A unified and integrated data platform that supports multi-workloads such as transactional, operational and analytical simultaneously in real-time, leveraging in-memory capabilities including…
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Meltdown and Spectre and Volt Active Data
Read more: Meltdown and Spectre and Volt Active DataThe internet is ablaze with articles and talk about hardware security flaws found recently in most modern processors, including chips from Intel and AMD – that is, in the processors used by everyone who runs software to provide a service. In other…
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NoSQL, RDBMS, and Contention for Shared Data: Part 2
Read more: NoSQL, RDBMS, and Contention for Shared Data: Part 2Previously in part one of this blog series, I explained the problems with two methods of database interactions. Traditional JDBC-style interactions mean that locking and latching take up ~30% of compute time. This overhead skyrockets when you try to use a distributed system.…
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NoSQL, RDBMS, and Contention for Shared Data: Part 1
Read more: NoSQL, RDBMS, and Contention for Shared Data: Part 1First off: I’m not here to bash NoSQL. NoSQL came into existence for a good reason — your generic legacy SQL RDBMS is often slow and expensive when compared to NoSQL alternatives. But much of the discussion I’ve seen about NoSQL, NewSQL,…
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8 Tips for Evaluating a Database in 2022
Read more: 8 Tips for Evaluating a Database in 2022It’s that time of year — the “wrap up/planning” blogs are among us as we look to a new year. With that, Volt Active Data has decided to put together a few tips and recommendations to consider when evaluating database technologies in…
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Microservices – What CSPs can Learn From IT
Read more: Microservices – What CSPs can Learn From ITCSPs are in a critical period of transformation right now. Omnipresent connectivity is driving new disruptive business models which are further driving up demands on the networks. Virtualization of appliances and systems is seen as a necessary step to add the agility…
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The Changing Landscape of Databases in Financial Services
Read more: The Changing Landscape of Databases in Financial ServicesFor decades, relational databases was the de-facto choice for financial service companies, until the 2000s where systems started to face challenges with scalability and availability as the amount of data being processed and consumed shaped how companies conducted their business. NoSQL databases…
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Volt Active Data Bonded Network Compatibility
Read more: Volt Active Data Bonded Network CompatibilityIn this post we describe Volt Active Data’s high availability architecture and how it interacts with bonded networks. Together they offer protection and continuity against network failovers. How do we know? Because we tested it and describe the tests we ran to…
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Key Considerations for a Modern Database to Operate at Scale
Read more: Key Considerations for a Modern Database to Operate at ScaleModern applications have two primary needs: Performance The performance consists of two aspects: throughput and latency. Both are driven by applications becoming machine-driven i.e. API-driven. Humans will wait much longer than an API will since APIs have strict latency expectations due to…
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