
8 min read
OEMs face incredible challenges today. They’re being asked to do more with less as supply chain and operation overrun issues create a legitimate OEM crisis. And yet, more often than not, OEMs don’t consider their underlying tech stack technologies until they are…

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Acid transactions, 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…

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Introduction NoSQL databases became “en mode” some time around 2012 and sprouted a database revolution that led many enterprises to replace their traditional RDBMS technology with NoSQL-based data platforms. What’s interesting now is how many of these companies are either regretting their…

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In February, Hewlett Packard Enterprise (HPE) launched a new Enterprise Communications Technology Group (CTG) to help telcos and enterprises capitalize on the 5G opportunity. As a partner of HPE, the Volt Active Data team couldn’t be more excited about this development and…

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Business support systems (BSS)—specifically, charging and policy functions—hold the key to monetizing 5G investments for telecommunications companies and their partners. However, for this key to unlock new revenue for communication service providers (CSPs), there are a couple of things that need to…

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Redis recently announced a US$100M round of funding; a positive sign for the industry, especially in the current challenging environment. In the article, co-founder and CTO Yiftach Shoolman states ambitiously that “If latency is important, you should think twice before you use…

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In today’s digitally driven world, processing streaming data in real-time is a requirement for business success. The introduction of 5G networks will only increase the data volume and speed requirements that are already putting pressure on traditional data architectures. Organizations need to…

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Traditional pub/sub systems such as Apache Kafka (and their numerous ever evolving stream processing avatars like Apache Samza, Apache Storm, Apache Flink, etc.) work fine for a bunch of simple use cases where there is a need for simple decisions, speed, scale…

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There is a massive difference between generating the input data needed by a Machine Learning model once (to prove a concept), and doing it continuously, indefinitely, at scale, and within short time periods. Years of experience working with disparate and imperfect data…

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Recently Forrester group has started to talk about “translytics” and Translytical Databases – databases that can “Deliver Analytics At The Speed Of Transactions”. Is this more marketing hype? Or is there something to it? A traditional OLTP database handles lots of rapid fire…
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For 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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Credit card fraud is ever-growing and ever-present. According to the 2016 LexisNexis True Cost of Fraud study, the total cost per dollar of fraud losses has reached $2.40. The total cost of fraud as a percentage of revenue has continued to rise…