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Insights and Updates

Read the HarperDB teams’ thoughts on database technology topics such as SQL, NOSQL, Edge Computing, IoT, Industry 4.0, and more

2019 Predictions, A Look Ahead

January 02, 2019

Happy New Year! With 2019 full of possibilities ahead, we wanted to share our thoughts on where we see Technology moving in the upcoming year.  

 

Smarter Edge

The edge has been limited in functionality and performance mainly due to limited resources on each device.   Sure, most devices are significantly more powerful than the machines that got us to the moon , but modern applications have also become exponentially more resource intensive.
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IoT: In the Cloud and on the Edge

August 06, 2018
 
The Internet of Things (IoT) is inherently edge biased. The “things” are all devices out in the world, not encased in a high-tech data center. Naturally, we expect initial data collection to take place on these devices, but what happens after that? Where does the data go? How is it processed? Is the data processed? Is any value derived from that data? These are all questions I think about every time I talk with customers looking to find a solution for their IoT data.
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5 Common Mistakes in IoT Sensor Data Analytics

July 24, 2018
 
 
At this point I think it s a given that everyone is excited about IoT.  Consumers are excited because their 6 year old daughters can accidentally order $170 doll houses with Alexa and businesses are excited because they can see results like 92% increase in labor utilization.  
 
That said, if we are being honest , most organizations while hugely interested in IoT , are struggling with how to put it in place.   This is due to the fact that they are hitting some common roadblocks when it comes to gaining actionable insights from their IoT s ensor d ata. 

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5 Things You Can Improve with Parallel Computing

July 10, 2018
The easy way to solve a performance problem in technology seems to be to just get a bigger, better, faster computer. That’s what I told my mom when her Chromebook died. She hated that thing, so it was probably for the best. It’s also what everyone seems to do when their cloud service isn’t running fast enough. Get a bigger server, pay for a larger instance, etc. I get it, it’s simple and low effort, but it’s also expensive. Compute cost doesn’t scale linearly ; it scales exponentially, so instead of buying a super computer you could buy tons of average servers. The solution is much cheaper when parallelization can be used to solve large computing problems.
 
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