Introducing Crunchy Data Warehouse: A next-generation Postgres-native data warehouse. Crunchy Data Warehouse Learn more
Elizabeth ChristensenChristopher Winslett
Elizabeth ChristensenChristopher Winslett
Histograms were first used in a lecture in 1892 by Karl Pearson — the godfather of mathematical statistics. With how many data presentation tools we have today, it’s hard to think that representing data as a graphic was classified as “innovation”, but it was. They are a graphic presentation of the distribution and frequency of data. If you haven’t seen one recently, or don’t know the word histogram off the top of your head - it is a bar chart, each bar represents the count of data with a defined...
Read MoreElizabeth ChristensenDoug Hunley
Elizabeth ChristensenDoug Hunley
The Center for Internet Security (CIS) releases security benchmarks to cover a wide variety of infrastructure used in modern applications, including databases, operating systems, cloud services, containerized services, and even networking. Since 2016 Crunchy Data has collaborated with CIS to provide this security resource for those deploying Postgres. The output of this collaboration is a checklist for folks to follow and improve the security posture of Postgres deployments. The PostgreSQL CIS...
Read MoreElizabeth Christensen
Elizabeth Christensen
Working on big data loads and or data type changes can be tricky - especially finding and correcting individual errors across a large data set. Postgres versions, 16, 17, and newer have a new function to help with data validation: . is a sql function that can be queried that will determine if a given input can be parsed into a specific type like numeric, date, JSON, etc. Here’s a super basic query to ask if ‘123’ is a valid integer. This function gives a t-true and f-false response. So if I as...
Read MoreElizabeth Christensen
Elizabeth Christensen
Materialized views are widely used in Postgres today. Many of us are working with using connected systems through foreign data wrappers, separate analytics systems like data warehouses , and merging data from different locations with Postgres queries. Materialized views let you precompile a query or partial table, for both local and remote data. Materialized views are static and have to be refreshed. One of the things that can be really important for using materialized views efficiently is inde...
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I can’t get through a zoom call, a conference talk, or an afternoon scroll through LinkedIn without hearing about vectors. Do you feel like the term vector is everywhere this year? It is. Vector actually means several different things and it's confusing. Vector means AI data, GIS locations, digital graphics, and a type of query optimization, and more. The terms and uses are related, sure. They all stem from the same original concept. However their practical applications are quite different. So...
Read MoreElizabeth Christensen
Elizabeth Christensen
Postgres is being used more and more for analytical workloads. There’s a few hidden gems I recently ran across that are really handy for doing SQL for data analysis, and . Rollup and cube don’t get a lot of attention, but follow along with me in this post to see how they can save you a few steps and enhance your date binning and summary reporting. We also have a web based tutorial that covers Postgres Functions for Rolling Up Data by Date if you want to try it yourself with a sample dat...
Read MoreElizabeth Christensen
SQL makes sense when it's working on a single row, or even when it's aggregating across multiple rows. But what happens when you want to compare between rows of something you've already calculated? Or make groups of data and query those? Enter window functions. Window functions tend to confuse people - but they’re a pretty awesome tool in SQL for data analytics. The best part is that you don’t need charts, fancy BI tools or AI to get some actionable and useful data for your stakeholders. Window...
Read MoreElizabeth Christensen
Elizabeth Christensen
If you missed the database news lately, you could have missed that we just fused DuckDB with Postgres to build a really fast analytics platform based on Postgres. There’s so many interesting things you can do with this platform so expect to hear from me again 😉. Today I just want to show off one really simple trick for getting big data sets or training data into Postgres through Hugging Face. Hugging Face is a community repository of datasets, LLMs, models and other resources for Machine L...
Read MoreElizabeth Christensen
Elizabeth Christensen
As I’ve been working with Postgres psql cli, I’ve picked up a few good habits from my Crunchy Data co-workers that make my terminal database environment easier to work with. I wanted to share a couple of my favorite things I’ve found that make getting around Postgres better. If you’re just getting started with psql, or haven’t ventured too far out of the defaults, this is the post for you. I’ll walk you through some of the friendliest psql settings and how to create your own preset settings file...
Read MoreElizabeth Christensen
Elizabeth Christensen
Many folks are surprised to hear that Postgres has parallel queries out of the box. This was released in small batches across a half dozen versions of Postgres, so the major fanfare for having parallelism got a little bit lost. By default Postgres is configured for two parallel workers. The Postgres query planner will assemble a few plans for any given query and will estimate the additional overhead of performing parallel queries, and make a go or no-go decision. Depending on the settings and th...
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