Node, Postgres, MassiveJS - a Better Database Experience

First some background–I’ve always had a bit of a love hate relationship with ORMs. ORMs are great for basic crud applications, which inevitably happens at some point for an app. The main two problems I have with ORMs is:

  1. They treat all databases as equal (yes, this is a little overgeneralized but typically true). They claim to do this for database portability, but in reality an app still can’t just up and move from one to another.
  2. They don’t handle complex queries well at all. As someone that sees SQL as a very powerful language, taking away all the power just leaves me with pain.

Of course these aren’t the only issues with them, just the two ones I personally run into over and over.

In some playing with Node I was optimistic to explore Massive.JS as it seems to buck the trend of just imitating all other ORMs. My initial results–it makes me want to do more with Node just for this library. After all the power of a language is the ecosystem of libraries around it, not just the core language. So let’s take a quick tour through with a few highlights of what makes it really great.

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Seeding a Sharing-economy or Platform Company

These days if you’re creating a company you likely hope to accomplish more with less people, two ways of doing this fall to: The sharing economy and creating a platform. It’s easy to see the case for this when you have such unicorns like AirBnB or Uber. The opportunity for each of those to compete against hotel chains or taxi services which each need to manage their own inventory is incredibly exciting and revolutionary. In a similar fashion platforms can offer much the same, Heroku’s platform and marketplace made it easier than ever for developers to click a button and get everything they needed years ago. It’s not just their code, it’s everything from Postgres to Mongo to Logging. Or take the app store as example. Smart phones weren’t a new thing when the iPhone came out, but it was only the saviest of users that had apps installed on their windows smartphone or blackberry. The app store made the iPhone different than any other phone by allowing others to build and improve it, turning the iPhone not into a phone but a platform.

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A Guide to Analyst Relations for Startups

When it comes to go to market and marketing there’s lots of pieces in a toolchest that all work together. One that comes a bit later, but if used properly (much like a PR agency) can be valuable is industry analysts. And while working with a PR agency can quickly start to become clear. How to work with analysts so it is productive on both sides can take a bit longer to figure out, or at least it did for me. Even before you do start working with them there’s the question of if or when should you. Here’s hoping this primer makes it a bit faster and easier for others.

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A Guide to PR for Startups

You’ve built your product and you’re now ready for your first major launch. Or you’ve been through a launch or two, but are looking to scale the process as you’re doing more launches and announcements. You really have two options: do it all on your own, or work with a PR agency. One frequent crossroad is that you’re not at the point of a full time PR person, but unsure what a PR agency can offer you; and, further what’s the best way to work with them so you’re getting the maximum value.

As I’ve talked to more startups lately, it’s become clear that effectively working with PR teams and the media is mostly learned by doing. Because there’s not much guidance out there, here’s an attempt at some basic guidelines.

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Moving Past Averages in SQL (Postgres) – Percentiles

Often when you’re tracking a metric for the first time you take a look at your average. For example what is your ARPU – Average Revenue Per User. In theory this tells you if you can acquire new user how much you’ll make off that user. Or maybe what’s your average life time value of a customer. Yet, many that are more familiar looking and extracting meaning from data median or a few different looks at percentiles can be much more meaningful.

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Upsert Lands in PostgreSQL 9.5 – a First Look

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 Postgres 9.5 being released, anywhere from 3-6 months as a best guess. That doesn’t mean we can’t take a first look at this feature. Though before we get into it a few special call outs of thanks to Peter Geoghegan of the Heroku Postgres team for being the primary author on it, Andres Freund who recently just joined Citus Data for his heavy contributions, and Heikki Linnakangas as well for his contributions.

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A Product Management Blueprint

I find myself having more conversations with startups – both small and large – about product management. I’ve blogged about some of the tools in my chest here but I haven’t talked much about my “blueprint” for product management, which I find myself laying out in many conversations over coffee. What follows is this process I’ve used a few times over with new teams to get product and engineering moving together, shipping in a predictable manner, and tackling bigger and more strategic projects.

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A Simple Guide for DB Migrations

Most web applications will add/remove columns over time. This is extremely common early on and even mature applications will continue modifying their schemas with new columns. An all too common pitfall when adding new columns is setting a not null constraint in Postgres.

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My Wishlist for Postgres 9.5

As I followed along with the 9.4 release of Postgres I had a few posts of things that I was excited about, some things that missed, and a bit of a wrap-up. I thought this year (year in the sense of PG releases) I’d jump the gun and lay out areas I’d love to see addressed in PostgreSQL 9.5. And here it goes:

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When to Ship It, When to Kill It

A few weeks ago at lunch I had the opportunity to catch up with a company in the current YC batch, building something very similar to dataclips. While we talked about a lot of things from what we’ve learned from dataclips, marketing, and other areas. One area we talked about was product and when to ship vs. when to kill things and I realized I hadn’t talked on my fairly simple but clear view on this publicly, so here it is.

A large credit to Adam Wiggins for giving this model early on in Heroku and his approach to shipping product.

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