Crunchy Bridge now has database insights to keep track of key performance indicators for your Postgres database. From database tools like slow queries and cache hit ratio, to machine stats like CPU and IOPS, and a production check. We are making database management easier than ever.
We are excited to release version 5.4 of Crunchy Postgres for Kubernetes with support for ARM processors, pgvector, huge pages, Postgres tablespaces, and more.
Greg continues with more puzzles and solutions for the Advent of Code series, today covering day 18's puzzle. Greg has some amazing functions for surface area, heat maps, and 3d visualizations.
Chris has some tips on helping you get the most out of queries when working with a remote Postgres foreign data wrapper. He has an overview of how queries are executed with the fdw and then samples for using CTEs, sub-queries, materialized views, and more.
Greg continues with Advent of Code series, this one is puzzle 17. This one works with falling rocks. Using sequences, arrays, and aggregates he makes a stackable objects with nothing but SQL!
Skewed or uneven data is common in Postgres. Elizabeth has a quick query for finding your data distributions and recommendations on fixing indexes if you have skewed data.
Want to get CSV data into your database? Paul has some great tools to help you use CSV and Google Sheets. Like remote copy, http access, using Python for materialized views, and ogr_fdw. You heard that right, there's a foreign data wrapper for CSV to Postgres!
pgBackRest has some new features that allow you to bundle files in your backup repo and do a block incremental storage. These can really help with storage efficiency and performance. David has some sample code to help you get started.
CI/CD tools can help you deploy, test, and promote databases. Bob has a sample set up of using ArgoCD with Crunchy Postgres for Kubernetes. He even provides a really nice sidecar testing container for you to use.
Hyperloglog is a Postgres extension for doing high-compression storage and query approximations. Chris shows you how to get started building a metrics system inside your Postgres database while saving on storage space and query time.
Postgres 16 is in beta and we are all excited about the updated logical decoding features. You heard that right, you can now do logical replication from a non-primary database! Roberto takes us through an example setup for this.
We are excited to announce a new set of functions to generate svgs from Postgres and PostGIS! This gives you really easy maps, images, or charts directly from your database. Once you start reading through these samples, you'll want to start playing with images from your database.
Are you using tags in your database with some of your main database properties? Paul reviews some of the ways to store tags in a database from basic relational models to text arrays. He provides some performance tests, sample queries, and guidance on choosing the best path.
When was this table created? Greg dives into the 5 places where you can get information about Postgres object creation.
Use some of the newest AI tools for Postgres! Craig shows you how to use ChatGPT for schema creation, data creation, query writing, indexing and more.
A primer on working with time in Postgres. Covers data types, query formats, intervals, overlaps, range types, indexing, and roll ups.
Postgres can be a great back end to powering your customer-facing analytics. Craig gives an overview of getting started with a metrics schema and then powering up to performance.
AI has exploded the amount of vector data being generated. Getting performance can be uncertain, until you know the keys. Chris explains the 3 basics you need to get performance out of vector data with Postgres.
Craig gives us an introduction to working with Postgres in expanded contexts like analytics, metrics, log storage, and event data.
Chris has some tips for working with Ruby on Rails and ActiveRecord and using better SQL to improve performance and avoid N+1 queries.