Jesse Soyland
Jesse Soyland
There’s a couple super common Postgres errors you’re likely to encounter while using this database, especially with an application or ORM. One is the PG::DiskFull: ERROR: could not resize shared memory segment. It will look something like this. We see a good amount of support tickets from customers on this topic. If you see this error pass by in your logs. Don’t worry. Seriously. There’s no immediate reason to panic from a single one of these errors. If you’re seeing them regularly or all th...
Read MorePaul Ramsey
Paul Ramsey
Back in the 1990s, before anything was cool (or so my children tell me) and at the dawn of the Age of the Meme, a couple of college students invented a game they called the " Six Degrees of Kevin Bacon ". The conceit behind the Six Degrees of Kevin Bacon was that actor Kevin Bacon could be connected to any other actor, via a chain of association of no more than six steps. Why Kevin Bacon? More or less arbitrarily, but the students had noted that Bacon said in an interview that "he had worked...
Read MoreGreg Nokes
Greg Nokes
One of the major changes that the cloud brought to application and database management was the concept of "thin provisioning." With large amounts of compute or storage resources available behind an API, you can provision what you need now and expand your infrastructure as required. Frameworks like 12Factor and Cloud Native emerged to help developers leverage these new paradigms. In the past, these capabilities were only accessible to those leveraging public clouds. On-premises, with lead tim...
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 MoreÖnder Kalacı
Önder Kalacı
We recently introduced support for querying Iceberg tables from PostgreSQL in Crunchy Bridge for Analytics. Iceberg defines a way to store tables in data lakes (usually as Parquet files in S3) with support for snapshots and other important database features, and it is designed with high performance analytics in mind. If you’re new to Crunchy Bridge, it offers a fully managed PostgreSQL experience. Crunchy Bridge for Analytics extends these capabilities, enabling you to query and interact wit...
Read MoreMarco Slot
Marco Slot
In April we launched Crunchy Bridge for Analytics , which is a managed PostgreSQL option that enables fast and seamless querying of your data lake. Our initial release was focused on building a rock solid foundation for high performance analytics in PostgreSQL. We have since been hard at work turning it into a comprehensive analytics solution. Our goals in building Crunchy Bridge for Analytics are to: • Make it very easy to query data files (incl. Parquet/CSV/JSON/Iceberg) in object stores like...
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...
Read MoreDoug Hunley
Doug Hunley
Crunchy Data is pleased to announce the publication of the Crunchy Data PostgreSQL 16 Security Technical Implementation Guide (STIG) by the United States Defense Information Systems Agency (DISA). This update covers Postgres versions 13-16, for previous versions of Postgres see the prior Crunchy Data Postgres STIG . Crunchy Data has collaborated with DISA since 2017 on the PostgreSQL STIG and this new STIG reflects Crunchy Data's ongoing collaboration with DISA and commitment to provide enh...
Read MoreAndrew L'Ecuyer
Andrew L'Ecuyer
As a team you often get handed a piece of software to deploy and manage, for example Red Hat's Ansible Automation Platform (AAP) or Quay. Red Hat's guide is to run and manage this in OpenShift and great, you're already comfortable with OpenShift and have a decent size deployment. Turns out pretty early on you've got a decision to make you didn't even realize was a decision, what are you going to do about the database? Most software needs a database – and the database of choice is overwhelmingly...
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