inaka

Latest blog entries

/
20 Questions, or Maybe a Few More

20 Questions, or Maybe a Few More

Nov 16 2016 : Stephanie Goldner

/
The Power of Meeting People

Because conferences and meetups are not just about the technical stuff.

Nov 01 2016 : Pablo Villar

/
Finding the right partner for your app build

Sharing some light on how it is to partner with us.

Oct 27 2016 : Inaka

/
Just Play my Sound

How to easily play a sound in Android

Oct 25 2016 : Giaquinta Emiliano

/
Opening our Guidelines to the World

We're publishing our work guidelines for the world to see.

Oct 13 2016 : Brujo Benavides

/
Using NIFs: the easy way

Using niffy to simplify working with NIFs on Erlang

Oct 05 2016 : Hernan Rivas Acosta

/
Function Naming In Swift 3

How to write clear function signatures, yet expressive, while following Swift 3 API design guidelines.

Sep 16 2016 : Pablo Villar

/
Jenkins automated tests for Rails

How to automatically trigger rails tests with a Jenkins job

Sep 14 2016 : Demian Sciessere

/
Erlang REST Server Stack

A description of our usual stack for building REST servers in Erlang

Sep 06 2016 : Brujo Benavides

/
Replacing JSON when talking to Erlang

Using Erlang's External Term Format

Aug 17 2016 : Hernan Rivas Acosta

/
Gadget + Lewis = Android Lint CI

Integrating our Android linter with Github's pull requests

Aug 04 2016 : Fernando Ramirez and Euen Lopez

/
Passwordless login with phoenix

Introducing how to implement passwordless login with phoenix framework

Jul 27 2016 : Thiago Borges

/
Beam Olympics

Our newest game to test your Beam Skills

Jul 14 2016 : Brujo Benavides

/
Otec

Three Open Source Projects, one App

Jun 28 2016 : Andrés Gerace

/
CredoCI

Running credo checks for elixir code on your github pull requests

Jun 16 2016 : Alejandro Mataloni

/
Thoughts on rebar3

Thoughts on rebar3

Jun 08 2016 : Hernán Rivas Acosta

/
7 Heuristics for Development

What we've learned from Hernán Wilkinson at our Tech Day

May 31 2016 : Brujo Benavides

/
Introducing Dayron - The Elixir REST client you've always wanted

Meet our library to interact with RESTful APIs in your Elixir Applications.

May 24 2016 : Flavio Granero

/
Inaka's First Tech Day

Inaka's First Tech Day

May 20 2016 : Brujo Benavides

/
PictureViewMaster

The best image projector ever. Period.

May 18 2016 : The Gera

/
See all Inaka's blog posts >>

/
Don't Under-Think It: SQL vs NoSQL

Chad DePue wrote this on February 26, 2013 under design, dev, engineering, management, project .

Technical debt is the cost, in developer time or money, of a line of code due to poor engineering, sloppy programming, or cutting corners. It's everywhere in the technology world. I'm often asked to come in and solve problems due to massive technical debt.

Actual examples, from the obvious to the subtle:

  • A marketing website whose creator wasn't a developer and didn't understand that you could include files and therefore copied the same code into every page of the site. The creator was making significant money from the site and did not care that it had no structure as long as he could keep copying and pasting files to update.
  • A Ruby on Rails site with no administration pages. When the marketing managers wanted to change parts of the site, they used a database tool to go in and change individual lines in the database.
  • An iPhone application that uses a library that is no longer supported by the original developer, that used calls that Apple has subsequently disallowed, meaning that the owner of the app could no longer submit updates until the library was replaced.
  • A developer used Ruby on Rails and ActiveRecord and ignored any optimization of the SQL statements it generates. The site now has more than 40 servers, meaning that a small optimization at this point could significantly reduce operations costs.

In each example, an implicit or explicit choice was made. "Should I invest more time now either a) hiring a developer, b) building an admin, c) investigating a better supported library, or d) optimizing my SQL?" In each case, at the time and with the information available, the decision at the time was that it wasn't worth it.

Make the best decision at the time with the information available.


Often developers look at technical debt as something to be avoided. But I picked the four examples above for a very specific reason - they were all VERY profitable startups. I have many more examples of startups that over-engineered their version 1 product and failed. Correlation does not equal causation, but there's something to the idea that shipping a product into customer hands is much more important than engineering a long-term solution to a problem you don't yet have.

How does that relate to NoSQL?

The decision to avoid MySQL, PostgreSQL or other SQL stores is often connected with a fear that the SQL store won't support the traffic or load that the developer believes the app will have. The idea is that if you don't use SQL now, down the road it will be easier to add additional hardware and simply scale up the application. This is because databases like MongoDB and Riak allow sharding, and CouchDB has a simple-to-configure replication system. Typically NoSQL arguments focus on the two most egregious aspects of using a SQL store:

  • Addition of columns to an existing database table can be very slow and can cause downtime while it is happening. Even worse, on MySQL, these operations are not "transactional," meaning that you can't easily revert them if they don't go well.
  • If your database grows larger than one server can handle you have to start thinking of ways to redesign your app to "shard" the data into multiple databases by hand. This requires a lot of migration and application logic changes - and when you outgrow your first "shard", doing it again is even more painful.

So, there are some real reasons to consider alternatives to SQL, particularly if we believe we will have a MASSIVE amount of data. And each of these databases can be the right choice in certain applications. They each have significant pluses:

  • Riak makes adding additional space to your cluster as easy as adding another server. (They call them nodes).
  • MongoDB allows for relatively easy (not as easy as Riak but still - quite easy) sharding of data onto multiple servers.
  • CouchDB makes replicating data from one server to another - locally or across the internet - as easy as one HTTP POST.
  • For all three, there's no need to design a database schema up-front, and making a change that could take minutes of downtime to add another column to your database just doesn't exist. Simply start storing that new piece of data from your app.

The problem is that all of these come at a cost to the day-to-day productivity of the team. You can't query any of these the same way a SQL database is queried. An ad-hoc query on any of these that might take a minute to write in SQL will take far longer:

  • For CouchDB, ad-hoc queries are strongly discouraged and queries must be calculated across a database. For a big dataset, this can take hours. Certain operations can trigger a refresh of these pre-calculated queries and may make the server unresponsive at any point.
  • Riak Map/Reduce jobs across a substantial set of data (ie more than a few thousand keys) are not supported.
  • MongoDB specifically discourages real-time Map/Reduce jobs and doesn't guarantee performance.

In each case, if I under-think my database decision, I will be paying a daily tax per developer, per query, per feature of my app to avoid a theoretical longer-term debt of a difficult-to-scale SQL database.

I like to think of these little day-to-day Map/Reduce hassles as debt payments on a debt I haven't yet incurred.


What does that mean for the typical new application? When should we consider SQL and when should we consider an alternative?

  • If I am going to be doing "joins" between my data in any way, SQL is much, much easier to develop. Example: Users who have accounts and orders. Devices have photos. Friends can share with each other, etc.
  • If I just need a key/value store and don't care about searching that datastore, EVER, NoSQL is much more powerful. Example: Web sessions or per-device data that is always associated with a 'master key'.
  • If I think I might have to 'fan out' a lot of data - pushing subscriptions to a lot of users, using SQL with NoSQL can be powerful. Keep the list of subscriptions in SQL and the "inbox" in NoSQL. Example: Twitter-like applications with subscriptions.

It doesn't make sense to make debt payments before you have any debt.


About 80% of Inaka's applications use traditional SQL databases. 10% use Redis and the remainder use Riak, MongoDB, or CouchDB.

When we think NoSQL is the right tool, we generally recommend Riak because the community and enterprise support is so deep, and we believe in the tradeoffs that Riak makes to keep data safe.

We used to recommend NoSQL "out of the gate". We no longer do so because of the hidden costs of day-to-day development. It just doesn't make sense to make debt payments before you've incurred any debt.

This is loosely related to an earlier post. Read more here.

Contact Us

Follow Chad On Twitter