Vertica Blog

Vertica Blog

Under the Hood

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Finding Patterns in Stock Prices With Vertica

Vertica can ingest data from many sources and enable SQL-based preparation and analytics. Here is another real-world example: Let's use Vertica to find patterns in a public data set of stock and (Exchange-Traded Fund) ETF prices from Kaggle. I’ll use the following data source in this post: This data source provides several thousand files for...
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Complex Data Types in SQL 2 – Benefits of SQL Support

Co-authored by James Clampffer, Deepak Majeti. In this second post in the blog series, let’s look at some of the reasons complex types are used extensively in organized big data formats like ORC and Parquet. Be sure to read the in this series where we discussed the , and explored the various complex types in...

Vertica on the Road! Using Vertica to Prepare and Analyze Vehicle Telematics Data

Vehicles generate a lot of data from onboard electronics and there is increasing interest in monitoring vehicle handling to help assess insurance risk and premiums. At Vertica, we're working with a few auto manufacturers, so I built this demo to show a relatively simple example of data collection, aggregation and preparation, and analysis of the...

Announcing Vertica 9.3 Instructor-Led Training Courses

Just in time for the release of version 9.3, Vertica is pleased to announce the release of two updated instructor-led training courses: Vertica 9.3 Essentials and Vertica 9.3 Descriptive Analytics. A description of each course follows: Vertica 9.3 Essentials This 4-day course explores the capabilities of the Vertica platform solution in Enterprise mode, and prepares...

Checking and Improving Column Compression and Encoding

When working with terabytes of data, storage and transfer become major time and cost sinks. Vertica can help minimize storage cost and transfer time with column compression and encoding. How can we identify Vertica tables that might benefit from compression? Information about column size and current compression is stored across column_storage and projection_columns table. The...
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Complex Data Types in SQL 1 – What Are They?

Co-authored by James Clampffer, Deepak Majeti. A lot of projects require querying ORC or Parquet files, or other data that may have internal types that are a bit more complex than usual. We support some of those complex types now, and are dedicated to adding full support for all complex types in Vertica. It’s a...
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Announcing Vertica Version 9.3 – Ride the Winds of Change

The have been blowing strong. This week, Vertica version 9.3 made its big splash. Vertica has a tendency to pack a lot of features even into minor releases, and this is not a minor release. Rather than dive deep, I’m going to skim the surface of the ocean of new features. Eon Mode Improvements Eon...
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Extending Vertica with Python functions: Adding NumPy FFT as a UDx

User-Defined Transform Function (UDTF) support for Python UDx were added back in Vertica 9.1, allowing you to add a much greater range of existing libraries and functions to Vertica. In this example, I'll add Fast Fourier Transform (FFT) from the NumPy package. FFT is a way to transform time-domain data into frequency-domain data. My test...
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Vertica in Eon Mode Depot – Where Did You Go?

Separating compute from storage is such a hot topic these days. “Instance types” and “S3 Object Storage” are core to the language of the public clouds (unless you’re Azure, then substitute S3 with Blob but leave the Object Storage part). This next-generation architecture enables so many operational and economic advantages – workload isolation, elastic scaling,...
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The Vertica Academy Is Open for Learning

One of the greatest impacts from digital transformation, both from a personal and professional point of view, is not just the democratization of data - a very popular topic here at Vertica! - but the democratization of knowledge. Today, we are excited to announce the new, a platform that offers self-paced, technical training and certifications...
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In-Database Machine Learning 2: Calculate a Correlation Matrix – A Data Exploration Post

In the , we discussed some of the reasons why it makes sense to do your machine learning inside the database. This will be the first post where we discuss some of the steps involved in the in-database machine learning workflow. Generally, the first thing you need to do is explore your data. This can...
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Evaluating Classifier Models in Vertica

Co-authored by Elizabeth Michaud Vertica provides an out-of-the box machine learning toolset that covers a complete data science workflow. The toolset includes several distributed functions for evaluating both classifier and regressor machine learning models. The goal of this blog post is to demonstrate how you can use the built-in functions for evaluating the prediction performance...