Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Steve Pousty
Steve Pousty
Greetings friends! We have come to our final blog post in my series about the data science workflow using PostgreSQL. In the last blog post , we used PL/R to create a function which returns the output from a logistic regression model trained on our fire data. We then took that model object and stored it into a separate table. Today we are going to finish up by showing how to use that stored model to make predictions on new data. By the way, I did all of the Postgres work for the entire blog s...
Read MoreDouglas Hunley
Douglas Hunley
Crunchy Data is pleased to announce the publication of the Crunchy Data PostgreSQL Security Technical Implementation Guide ( STIG ) by the United States Defense Information Systems Agency ( DISA ). Crunchy Data collaborated with DISA to make PostgreSQL the first open source database to provide a published STIG in 2017, and this new STIG reflects Crunchy Data's ongoing collaboration with DISA to provide enhanced security guidance as PostgreSQL continues to advance and evolve. While the ST...
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Crunchy Data
This new guide is the result of ongoing collaboration with DISA and provides security guidance for PostgreSQL 9.6 through 12 Charleston, S.C. (January 6, 2021) - Crunchy Data — the leading provider of trusted open source PostgreSQL — is pleased to announce the release of the Crunchy Data PostgreSQL Security Technical Implementation Guide ( STIG ) by the United States Defense Information Systems Agency ( DISA ). In 2017, Crunchy Data collaborated with DISA to publish the initial version...
Read MoreSteve Pousty
Steve Pousty
Greetings friends! We have finally come to the point in the Postgres for Data Science series where we are not doing data preparation. Today we are going to do modeling and prediction of fire occurrence given weather parameters… IN OUR DATABASE! Quick recap: 1. We found some data on historical fires and historical weather data for California. 2. We fixed up the data and merged it to make it more appropriate for logistic regression. 3. We randomly sampled non-fire data and split the data int...
Read MoreKat Batuigas
Kat Batuigas
There are a lot of ways to load data into a PostgreSQL/ PostGIS database and it's no different with spatial data. If you're new to PostGIS, you've come to the right place. In this blog post, I'll outline a few free, open source tools you can use for your spatial data import needs. You can use a desktop GUI application like QGIS, and/or command-line utilities. If you want more flexibility, it's great to have both types in your toolkit. I'll talk about importing to PostGIS within the context of v...
Read MoreGreg Smith
Greg Smith
Some people are obsessed with sports or cars. I follow computer hardware . The PC industry has overclocking instead of nitrous, plexi cases instead of chrome, and RGB lighting as its spinning wheels. The core challenge I enjoy is cascading small improvements to see if I can move a bottleneck. The individual improvements are often just a few percent. Percentage gains can compound as you chain them together. Today I'm changing the memory speed on my main test system, going from 2133MHz to 3200MHz...
Read MoreKat Batuigas
Kat Batuigas
In this series so far we've talked about how to get our Django application to save uploaded images as bytea in Postgres . We've also walked through an example of a PL/Python function that processes the binary data to apply a blur filter to the uploaded image. Now, we'll show how to retrieve the blurred image from Django. Use the function in a SQL view mapped to a Django model Now that we have a PL/Python function, what do we do with it? The function lives in PostgreSQL, so we'll have to figure...
Read MoreKat Batuigas
Kat Batuigas
I recently wrote about building a Django app that stores uploaded image files in bytea format in PostgreSQL. For the second post in this series, we're now going to take a look at applying a blur filter to the uploaded image using PL/Python . Lately we've been wading into PL/Python waters, and want to learn how to process raw binary data using some popular Python libraries. Python has an almost dizzying array of options when it comes to data analysis and scientific computing. Pair that with...
Read MoreJonathan S. Katz
Jonathan S. Katz
What if I told you that you can create an out-of-the-box active-active, federated PostgreSQL cluster on Kubernetes? Since logical decoding was introduced in PostgreSQL 9.4, I have been fascinated by the various applications it has. In fact, I've used this feature to apply the concepts of change data capture both in theory and practice to the benefit of both applications and users. Logical replication and native partitioning support , introduced in Postgres 10, offered even more possibilit...
Read MorePaul Ramsey
Paul Ramsey
The PostGIS raster extension has a steep learning curve, but it opens up some unique possibilities for data analysis and accessing non-standard data from within PostgreSQL. Here's an example that shows how to access raster data from PostGIS running on Crunchy Bridge . The raster data type in PostGIS can be used to store any kind of raster data: images, elevation grids, model outputs, and more. One band, four band, multi-band and anything in between. This flexibility leads some beginners to du...
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