One of the unique characteristics of the recently launched Crunchy Bridge for Analytics is that it is effectively a hybrid between a transactional and an analytical database system. That is a powerful tool when dealing with data-intensive applications which may for example require a combination of low latency, high throughput insertion, efficient lookup of recent data, and fast interactive analytics over historical data. A common source of large data volumes is append-mostly time series data or event data generated by an application. PostgreSQL has various tools to optimize your database for t ..read more

A lot of the world’s data lives in data lakes, huge collections of data files in object stores like Amazon S3. There are many tools for querying data lakes, but none are as versatile and have as wide an ecosystem as PostgreSQL. So, what if you could use PostgreSQL to easily query your data lake with state-of-the-art analytics performance? Today we’re announcing Crunchy Bridge for Analytics, a new offering in Crunchy Bridge that lets you query and interact with your data lake using PostgreSQL commands via extensions, with a vectorized, parallel query engine. With Bridge for Analytics you can ea ..read more

You could be saving money every month on databases costs with a smarter data retention policy. One of the primary reasons, and a huge benefit of partitioning is using it to automatically archive your data. For example, you might have a huge log table. For business purposes, you need to keep this data for 30 days. This table grows continually over time and keeping all the data makes database maintenance challenging. With time-based partitioning, you can simply archive off data older than 30 days. The nature of most relational databases means that deleting large volumes of data can be very ineff ..read more

I recently created a Postgres extension which utilizes the pg_cron extension to schedule recurring activities using the cron.schedule(). Everything worked great. The only problem was when I dropped my extension, it left the cron job scheduled, which resulted in regular errors: 2024-04-06 16:00:00.026 EST [1548187] LOG: cron job 2 starting: SELECT bridge_stats.update_stats('55 minutes', false) 2024-04-06 16:00:00.047 EST [1580698] ERROR: schema "bridge_stats" does not exist at character 8 2024-04-06 16:00:00.047 EST [1580698] STATEMENT: SELECT bridge_stats.update_stats('55 minutes', false ..read more

Row-level security (RLS) in Postgres is a feature that allows you to control which rows a user is allowed to access in a particular table. It enables you to define security policies at the row level based on certain conditions, such as user roles or specific attributes in the data. Most commonly this is used to limit access based on the database user connecting, but it can also be handy to ensure data safety for multi-tenant applications. Creating tables with row level security We're going to assume our tenants in this case are part of an organization, and we have an events table with events t ..read more

I recently got my very first patch into PostgreSQL! To be clear I'm not a C developer and didn't contribute some fancy new feature. However, I do love Postgres and wanted to contribute. Here's my journey and what I learned along the way. Oh, something’s missing from docs! A patch idea ? I had an idea for a docs patch while I was talking to Stephen Frost about some research and writing I was doing about HOT updates and fill factor. A recent update to HOT updates meant HOT could be compatible with BRIN. And while the HOT readme was up to date, the main PostgreSQL docs were missing a reference to ..read more

Calculating distance is a core feature of a spatial database, and the central function in many analytical queries. "How many houses are within the evacuation radius?" "Which responder is closest to the call?" "How many more miles until the school bus needs routine maintenance?" PostGIS and any other spatial database let you answer these kinds of questions in SQL, using ST_Distance(geom1, geom2) to return a distance, or ST_DWithin(geom1, geom2, radius) to return a true/false result within a tolerance. SELECT ST_Distance( 'LINESTRING (150 300, 226 274, 320 280, 370 320, 390 370)'::geometry ..read more

Postgres is an amazing database system, but it does come with a five-year life cycle. This means you need to perform a major upgrade of it at least every five years. Luckily, Postgres ships with the pg_upgrade program, which enables a quick and easy migration from one major version of Postgres to another. Let's work through an example of how to upgrade - in this case, we will go from Postgres 12 to Postgres 16. You should always aim to go to the highest version possible. Check postgresql.org to see what the current version is. If you get stuck, the official documentation has a lot of details ..read more

Postgres is an amazing database system, but it does come with a five-year life cycle. This means you need to perform a major upgrade of it at least every five years. Luckily, Postgres ships with the pg_upgrade program, which enables a quick and easy migration from one major version of Postgres to another. Let's work through an example of how to upgrade - in this case, we will go from Postgres 12 to Postgres 16. You should always aim to go to the highest version possible. Check postgresql.org to see what the current version is. If you get stuck, the official documentation has a lot of details ..read more

While database migrations are not an everyday thing for you, they are for us. Migrating to a new database provider isn't something you ever take lightly. Once you've come to the decision that you may want to migrate then you look at the time and effort cost of switching and wonder if it's really worth it. You decide it is, and still you're left with uncertainty of what-if: What about Postgres versions? What about Postgres extensions? What about collations? How do you minimize cutover time while not spending 6 months doing some custom application double writing? What about performance, how do ..read more