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 entirely change the shape of this one. For a peek back of some of the past ones:

Last week I wrote up some initial steps for getting started with marketing a developer focused product. The short of it was quite trying to do “marketing” and just start putting out interesting material. A big part of this is sourcing material from your company’s developers. From there you want to gradually shift it from simply interesting technical posts to things that align with your core beliefs and add value to your customers.

Perhaps the easiest way to do this is by highlighting some examples of it.

Theres a lot of back and forth on NoSQL databases. The unfortunate part with all the back and forth and unclear definitions of NoSQL is that many of the valuable learnings are lost. This post isn’t about the differences in NoSQL definitions, but rather some of the huge benefits that do exist in whats often grouped into the schema-less world that could easily be applied to the relational world.

Forget migrations

Perhaps the best thing about the idea of a schemaless database is that you can just push code and it works. Almost exactly five years ago Heroku shipped git push heroku master letting you simply push code from git and it just work. CouchDB and MongoDB have done similar for databases… you don’t have to run CREATE TABLE or ALTER TABLE migrations before working with your database. There’s something wonderful about just building and shipping your application without worrying about migrations.

Commonly at developer focused companies the question from a marketing team will come up of “How do we get content that developers find interesting”? Or how can I get our developers to blog more? Or some other similar question. I general the question of creating content and engaging with developers is a very common one, and often theres a mismatch between what marketing wants to do and what developers appreciate.

Stop marketing

Forget trying to “market” to developers. Hopefully you at least have developers that believe in the product their building, if thats not the case then find a new product or a new team. If you’ve got a product targetted at developers and a team that believes in it then you’re already half way there to marketing it. Now back to the first point, forget trying to market it. Start with building some form of an audience, reputation, respect among other developers. This isn’t done through ads, email marketing, SEO or any of that. Its done by creating content that developers find interesting, as a first step forget your product entirely, but don’t worry we’ll get there soon enough.

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 simple feature actually makes SQL both readable and composable, and even for my own queries capable of coming back to them months later and understanding them, where previously they would not be.

The feature itself is known as CTEs or common table expressions, you may also here it referred to as WITH clauses. The general idea is that it allows you to create something somewhat equivilant to a view that only exists during that transaction. You can create multiple of these which then allow for clear building blocks and make it simple to follow what you’re doing.

Emails are one of my favorite methods of communicating with users. Its works as a quick test for product validation. It works well at one->some->many-> all. Its still highly effective even as much noise as we receive in our inboxes. Over the years I’ve tried a lot of email tools from custom built solutions, to newer entrants that help around drip actions (intercom.io and customer.io), to more “enterprise” tools such as Marketo. While I have varying opinions on all of those, I still find myself coming back to a simple one off script setup to deliver clear concise emails.

Just as PostgreSQL 9.3 was coming out I had a need to take advantage of the JSON datatype and some of the operators and functions within it. The use case was pretty simple, run a query across a variety of databases, then take the results and store them. We explored doing something more elaborate with the columns/values, but in the end just opted to save the entire result set as JSON then I could use the operators to explore it as desired.

Here’s the general idea in code (using sequel):

result = r.connection { |c| c.fetch(self.query).all }
mymodel.results = result.to_json

Several months back I wrote about how we do higher level, long term planning within the Heroku Postgres team. If you haven’t read the previous article please start there.

The exercise or rule of thirds is intended to be approximate prioritization and not a perfect science. Since that time I’m familiar with some teams both in and out of Heroku who have attempted this exercise with varying levels of success. We’ve now done this process 4 times within the team and after the most recent exercise attempted to take some time to internalize why its worked well, creating some more specifics about the process. Heres an attempt to provide even more clarity:

For a couple of years I’ve complained about the Postgres documentation and at the same time paraded it as one of the best sets of documentation I’ve encountered. In many ways the reason I veer towards Postgres as well as Python and Django is the quality of their documentation. If you need to find details about something its documented, and more importantly well and thoroughly documented.

In large part I came to Python by happenstance through Django, and Postgres through happenstance of an employer. Yet, Django was very little of an accident. The Django Tutorial got me a large part of what I needed to know and more excited about development than I had been in some time. Python has done some work at adding docs to make this even better, sadly its still very much needed for PostgreSQL.