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DataGals Year in Review

The DataGals had an amazing 2017! Everyone on our steering committee - Lisa Donaghue, Styliani Pantela, Soniya Shah, Diem Tran, and Sharada Vesta would like to wish you a very happy new year! Check out our year in review below. We look forward to a successful 2018. Happy holidays from the DataGals!

What’s New in Vertica 9.0.1?

This blog post was authored by Soniya Shah. In Vertica 9.0.1, we introduce new functionality including: • Eon Mode Beta Updates • Supported Platform Updates • Machine Learning Enhancements • Support for Ranger Integration • Security Enhancements • Backup, Restore and Recovery Updates Eon Mode Beta Updates In Vertica 9.0, we introduced Eon Mode Beta,...
Modern Database Analytics

External data is easier to manage than the Hadoop Stack

This blog post was authored by Steve Sarsfield. It has been a thrilling ride. In a few short years, Hadoop has seen astronomical rise, but recently, interest in Hadoop has peaked. Analysts like Gartner and Datanami are reporting that the hype in Hadoop is waning, with some hope that use cases for Hadoop will find...

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Programmer

Vertica in the Clouds

This blog post was authored by Soniya Shah. The benefits of using cloud computing and storage are virtually endless. You can scale services up or down to fit your needs, customize applications, and access cloud services from everywhere. Using the cloud makes it easy to scale elastically and makes infrastructure both affordable and flexible. With...
Commercial passenger plane with Vertica painted on the tail

Blog Post Series: Using Vertica to Track Commercial Aircraft in near Real-Time — Part 3

Building a Raspberry Pi to Capture ADS-B signals Picking apples, pears, blackberries or raspberries In a previous blog post, I provided a very high-level overview of ADS-B, and that with the appropriate pieces of hardware and some open-source software, it was possible to capture and decode the radio signals being broadcast from commercial aircraft, with...

Flattened Tables

This blog post was authored by Soniya Shah. Before release 8.1., Vertica users could denormalize their data by combining all fact and dimension table columns in a single 'fat' table. These tables facilitated faster query execution. However, this approach required users to maintain redundant sets of normalized and denormalized data, which incurred its own overhead....

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