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It feels like we’re starting to pass the peak of the hype cycle of microservices. It’s no longer multiple times a week we now see a blog post of “How I migrated my monolith to 150 services”. Now I often hear a bit more of the counter: “I don’t hate my monolith, I just care that things stay performant”. We’ve actually seen some migrations from micro-services back to a monolith. When you go from one
I’ve learned a lot of skills over the course of my career, but no technical skill more useful than SQL. SQL stands out to me as the most valuable skill for a few reasons: It is valuable across different roles and disciplines Learning it once doesn’t really require re-learning You seem like a superhero. You seem extra powerful when you know it because of the amount of people that aren’t fluent Let
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 respon
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
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
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
I find during the holiday season many pick up new books, learn a new language, or brush up on some other skill in general. Here’s my contribution to hopefully giving you a few new things to learn about Postgres and ideally utilize in the new year. It’s not in a top 10 list as much as 10 tips and tricks you should be aware of as when you need them they become incredibly handy. But, first a shameles
If you’ve followed anything I’ve written about Postgres, you know that I’m a fan. At the same time you know that there’s been one feature that so many other databases have, which Postgres lacks and it causes a huge amount of angst for not being in Postgres… Upsert. Well the day has come, it’s finally committed and will be available in Postgres 9.5. Sure we’re still several months away from Postgre
Theres no doubt that the 9.4 release of PostgreSQL will have some great improvements. However, for all of the improvements it delivering it had the promise of being perhaps the most impactful release of Postgres yet. Several of the features that would have given it my stamp of best release in at least 5 years are now already not making it and a few others are still on the border. Here’s a look at
PostgreSQL is currently entering its final commit fest. While its still going, which means there could still be more great features to come, we can start to take a look at what you can expect from it now. This release seems to bring a lot of minor increments versus some bigger highlights of previous ones. At the same time there’s still a lot on the bubble that may or may not make it which could en
SQL by default isn’t typically friendly to dive into, and especially so if you’re reading someone else’s already created queries. For some reason most people throw out principles we follow in other languages such as commenting and composability just for SQL. I was recently reminded of a key feature in Postgres that most don’t use by @timonk highlighting it in his AWS Re:Invent Redshift talk. The s
Postgres is rich with options for indexing. First you’ve got a variety of types, and beyond that you can do a variety of things with each of these such as create unique indexes, use conditions to index only a portion of your data, or create indexes based on complex expressions or functions. In cases where you commonly use various PostgreSQL functions in your application or reporting you can get so
If you missed my previous post on Understanding Postgres Performance its a great starting point. On this particular post I’m going to dig in to some real life examples of optimizing queries and indexes. It all starts with statsI wrote about some of the great new features in Postgres 9.2 in the recent announcement on support of Postgres 9.2 on Heroku. One of those awesome features, is pg_stat_state
A few weeks back I did a brief feature highlight on Postgres arrays. Since that time I’ve found myself using them with increasing regularity on small side projects. Much of this time I’m using Django and of course not opting to write raw SQL to be able to use arrays. Django actually makes it quite simple to work with Arrays in Postgres with a package by Andrey Antukh. Lets get started by installin
Yesterday there was a post which hit Hacker News that talked about using SQL to access Mongo. While this is powerful I think much of the true value was entirely missed within the post. SQL is an expressive language, though people are often okay with accessing Mongo data through its own ORM. The real value is that you could actually query the data from within Postgres then join across your data sto
Update theres a more recent post that expands further on where to start optimizing specific queries, and of course if you want to dig into optimizing your infrastructure High Performance PostgreSQL is still a great read For many application developers their database is a black box. Data goes in, comes back out and in between there developers hope its a pretty short time span. Without becoming a DB
This post is a list of many of the reasons to use Postgres, much this content as well as how to use these features will later be curated within PostgresGuide.com. If you need to get started check out Postgres.app for Mac, or get a Cloud instance at Heroku Postgres for free Last week I did a post on the many reasons to use Postgres. My goal with the post was two fold: Call out some of the historica
This post is a list of many of the reasons to use Postgres, much this content as well as how to use these features will later be curated within PostgresGuide.com. If you need to get started check out Postgres.app for Mac, or get a Cloud instance at Heroku Postgres for free UPDATE: A part 2 has been posted on Why Use Postgres Very often recently I find myself explaining why Postgres is so great. In
I alluded in earlier posts of How Heroku Works that we have talented engineers. In fact I would venture to say that there is not a weak link when it comes to our engineers at Heroku. Ensuring we have talented engineers makes it easier for us to find other talented engineers and maintains a level of quality in our product. This means we must be very careful about not diluting our pool of engineerin
In my earlier post on Teams and Tools at Heroku, I mentioned how we value engineers’ time; their work has enabled us to build a great platform. As a result of what we’ve built, we’ve had great growth both of our platform and of our teams internally. With that growth inevitably comes different distractions on engineers’ time. Despite how a manager may plan things, engineering work needs long period
Heroku is a largely agile company, we work in primarily small teams that talk via api and data contracts. Its also a company comprised primarily of engineers, even product managers often write code. Heroku as a platform drives many of the features not from top down, but from bottom up based on engineers desires or skunkworks projects. There’s many valuable insights into how Heroku runs efficiently
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