Many of us have known how great Postgres was for years.

In fact I recall a conversation with some sales engineers about 6 years ago that previously worked for a large database vendor that really no one likes down in Redwood City. They were remarking how the biggest threat to them was Postgres. At first they were able to just brush it off saying it was open source and no real database could be open source. Then as they dug in they realized there was more there than most knew about and they would have to continually be finding ways to discredit it in sales conversations. Well it doesn’t look like those SEs or the rest of that company was too successful.

Postgres has a rich set of features, even when working everyday with it you may not discover all it has to offer. In hopes of learning some new features that I didn’t know about myself as well as seeing what small gems people found joy in I tweeted out to see what people came back from. The response was impressive, and rather than have it lost into ether of twitter I’m capturing some of the responses here along with some resources many of the features.

In my career I’ve had to conduct a number of retrospectives. Ahead of them it already sucked, there was an outage at some point, customers were impacted, and it was our fault. Never was it solely on our underlying infrastructure provider (AWS or Heroku), nope the blame was on us and we’d failed in some way. And as soon as the incident was resolved, it wasn’t time to go home and decompress with a beer, it was time start the process of a retrospective.

Finding the motivation to get right back to work is tough, but not losing time is important. There is probably a lot out there on retrospectives, and in general I was well rehearsed at them. But since I’d not performed a large scale one in a few years I found myself rusty and thought it’d be good to share some of our process.

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.