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Harmonizing Space, Time, and Semantics: Navigating the Complexity of Geo-Distributed IoT Databases

DZone

In the era of the Internet of Things ( IoT) , the continuous influx of spatial and temporal data from interconnected devices has given rise to a vast and intricate landscape, demanding a sophisticated approach to database management.

IoT 278
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Log4j 2 Vulnerability: Identifying and Minimizing Production Risk

Dynatrace

The National Vulnerability Database describes the exploit here. As organizations work to find the usage of this library in their applications, they should focus on three criteria to prioritize the fix in their environment: Public Internet Exposure – Are the Java processes using these libraries directly accessible from the internet?

Java 241
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Log4Shell vulnerability: Identifying and minimizing production risk

Dynatrace

The National Vulnerability Database describes the vulnerability here. As organizations work to find the usage of this library in their applications, they should focus on three criteria to prioritize the fix in their environment: Public Internet Exposure – Are the Java processes using these libraries directly accessible from the internet?

Java 187
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Stuff The Internet Says On Scalability For October 5th, 2018

High Scalability

Because the device in question is a high-speed unit designed to process a high volume of ballots for an entire county, hacking just one of these machines could enable anattacker to flip the Electoral College and determine the outcome of a presidential election?. They'll love it and you'll be their hero forever. So many more quotes.

Internet 156
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What Should You Know About Graph Database’s Scalability?

DZone

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios. Do Not Be Misled Designing and implementing a scalable graph database system has never been a trivial task.

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Stuff The Internet Says On Scalability For November 23rd, 2018

High Scalability

Waqas Dhillon : The goal of in-database machine learning is to bring popular machine learning algorithms and advanced analytical functions directly to the data, where it most commonly resides – either in a data warehouse or a data lake. Can you eat more after Thanksgiving? Lots of leftovers.

Internet 174
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

Big Data 154