Postgres is an interesting open source project. It’s truly one of a kind, it has its own license to prove it as opposed to falling under something like Apache or GPL. The Postgres community structure is something that is pretty well defined if you’re involved in the community, but to those outside it’s likely a little less clear. In case you’re curious to learn more about the community here’s a rundown of a few various aspects of it:

Dear Postgres,

I’ve always felt an affinity for you in my 9 years of working with you. I know others have known you longer, but that doesn’t mean they love you more. Years ago when others complained about your rigidness or that you weren’t as accommodating as others I found solace in your steadfast values:

1. Don’t lose data
2. Adhere to standards
3. Move forward with a balancing act between new fads of the day while still continuously improving

You’ve been there and seen it all. Years ago you were being disrupted by XML databases. As companies made heavy investment into what such a document database would do for their organization you proceeded to “simply” add a datatype that accomplished the same and brought your years of progress along with it.

Managing connections in Postgres is a topic that seems to come up several times a week in conversations. I’ve written some about scaling your connections and the right approach when you truly need a high level of connections, which is to use a connection pooler like pgBouncer. But what do you do before that point and how can you better track what is going on with your connections in Postgres?

As your database grows and scales there are some operations that you need to take more care of than you did when you were just starting. When working with your application in your dev environment you may not be fully aware of the cost of some operations until you run them against production. And at some point most of us have been guilty of it, running some migration that starts at 5 minutes, then 15 minutes in it’s still running, and suddenly production traffic is impacted.

There are two operations that tend to happen quite frequently, each with some straightforward approaches to mitigate having any noticable amount of downtime. Let’s look at each of the operations, how they work and then how you can approach them in a safer way.

It’s not a very disputed topic that you should backup your database, and further test your backups. What is a little less discussed, at least for Postgres, is the types of backups that exist. Within Postgres there are two forms of backups and understanding them is a useful foundation for anyone working with Postgres. The two backup types are

1. Physical: which consist of the actual bytes on disk,
2. Logical: which is a more portable format.

Let’s dig into each a bit more so you can better assess which makes sense for you.

This year Postgres open and PGConf SV have combined to great a bigger and better conference right in downtown San Francisco. I’m obviously biased as I’m one of the co-chairs, and I know every conference organizer says picking the talks was hard, but I’m especially excited for the line-up this year. The hard part for me is going to be which talks do I miss out on because I’m sitting in the other session that’s ongoing. You can see the full list of talk and tutorial sessions, but I thought it’d be fun to do a rundown of some of my favorites.

A massive amount of reporting queries, whether really intensive data analysis, or just basic insights into your business involving looking at data over a certain time period. Postgres has really rich support for dealing with time out of the box, something that’s often very underweighted when dealing with a database. Sure, if you have a time-series database it’s implied, but even then how flexible and friendly is it from a query perspective? With Postgres there’s a lot of key items available to you, let’s dig in at the things that make your life easier when querying.

Five years ago I wrote a post that got some good attention on why you should use Postgres. Almost a year later I added a bunch of things I missed. Many of those items bear repeating, and I’ll recap a few of those in the latter half of this post. But in the last 4-5 years there’s been a lot of improvements and more reasons added to the list of why you should use Postgres. Here’s the rundown of the things that make Postgres a great database you should consider using.

JSONB is an awesome datatype in Postgres. I find myself using it on a weekly basis these days. Often in using some API (such as clearbit) I’ll get a JSON response back, instead of parsing that out into a table structure it’s really easy to throw it into a JSONB then query for various parts of it.

If you’re not familiar with JSONB, it’s a binary representation of JSON in your database. You can read a bit more about it vs. JSON here.

In working with JSONB here’s a few quick tips to get up and running with it even faster:

It seems each week when I’m reviewing data with someone a feature comes up that they had no idea existed within Postgres. In an effort to continue documenting many of the features and functionality that are useful, here’s a list of just a few that you may find handy the next time your working with your data.

Psql, and \e

This one I’ve covered before, but it’s worth restating. Psql is a great editor that already comes with Postgres. If you’re comfortable on the CLI you should consider giving it a try. You can even setup you’re own .psqlrc for it so that it’s well customized to your liking. In particular turning \timing on is especially useful. But even with all sorts of customization if you’re not aware that you can use your preferred editor by using \e then you’re missing out. This will allow you to open up the last run query, edit it, save–and then it’ll run for you. Vim, Emacs, even Sublime text works just take your pick by setting your $EDITOR variable.