Rails 3 Slave Databases: Compare Octopus to SDP

In the crazy wild days of Rails 2.x…

In the pre-Rails 3 ecosystem, there were a number of confusingly similar choices for getting master/slave database functionality established. These options included Masochism, DB Charmer, master_slave_adapter, and seamless_database_pool, amongst others. When it came time from Bonanza to make its choice on which slave plugin to use, I made my best effort to assess the velocity and functionality of each of the prominent slave database solutions, and wrote what went on to become a fairly popular post comparing the relative strengths of each choice.


Fast forward to Rails 3, and the field has narrowed considerably. Most all of the top Google results for Rails slave database options these days point to Octopus, and with good reason. Its documentation is sound, and its github project has maintained good velocity for the better part of the past year. Reading between the lines of the Octopus documentation, it would seem that it was built first and foremost as a tool to make it stupidly easy to shard databases; secondarily, it also supports using slave databases in a non-sharding format, but the implementation here gets a little more sketchy, as the examples show users needing to explicitly declare a given slave database for a particular query. In the documentation, this is done at query time, e.g.,

User.where(:name => "Thiago").limit(3).using(:slave_one)


Octopus.using(:slave_two) do
  User.create(:name => "Mike")

Seamless Database Pool

Upon learning about octopus, my natural inclination was to compare it to our current solution, seamless_database_pool. Admittedly, when we got to the Rails 3 party, SDP was running a bit behind. The author had been kind enough to do much of the legwork to get it compliant with AR3, but we still encountered errors actually trying to use the plugin within controllers and views the way we had been able to with the previous version.

So I fixed it.

What Seamless Database Pool now represents is a slave database plugin that is specifically built with the purpose of making it as easy as possible to A) connect to one or more weighted slave databases B) declare whether a particular Rails action should attempt to use slaves, masters or both (automatically defaulting to the master when write operations occur) and C) gracefully handle failover if one or more of the slave databases declared should become unavailable for whatever reason.

SDP does not have any built in support for sharding, so if that is what your DB needs, Octopus is your best bet. But if what you need is specifically a Rails 3 supported solution that will allow you to connect mix and match your main database and N number of slaves, in a weighted way and with failover automatically baked in, this is where seamless_database_pool really shines.

Bonanza has been using SDP in production for more than a year now, and in the meantime have experience failures of our slave database every few months, which at one point what have brought down the entire site. Now, within seconds, Rails figure out that it needs to re-route requests and finds a database it can use that is still available. The still-good SDP documenation describes how to make it happen.

Bottom line

Prior to writing this blog, if you Google master/slave database you would probably come away thinking there was only one solution, and that solution was only secondarily focused on allowing N slaves to be configured. I may be wrong about the level of support that Octopus already had for setting up multiple weighted failover slaves (and being able to declare usage of these on a per-action vs. per-query basis), but the documentation makes me think that this is at best a future roadmap feature. In the meantime, if it’s specifically database support you need, try the drag-and-droppable SDP gem. I will continue linking my fork of the project until the original author decides what he wants to do with my pull request (which fixes fundamental issues with Rails 3 controller integration, plus adds more robust slave failover).


Is as easy as possible. In your bundler Gemfile:

gem “seamless_database_pool”, :git => “git://github.com/wbharding/seamless_database_pool.git”

Your database.yml file will then look something like:

  adapter: seamless_database_pool
  port: 3306
  username: app_user
  password: app_pass
  pool_adapter: mysql
    pool_weight: 0 # 0 means we only use master for writes if the controller action has been setup to use slaves
    - host:
      username: slave_login
      password: slave_pass

Do drop a line in the comments with any questions or feedback if you have experience with either SDP or Octopus as solutions for Rails slave database support!

Rails 3 Performance: Abysmal to Good to Great

So you’ve upgraded from Rails 2.x to Rails 3 and you’re not happy with the response times you’re seeing? Or you are considering the upgrade, but don’t want to close your eyes and step into the great unknown without having some idea what to expect from a performance standpoint? Well, here’s what.

Performance in Rails 2.2

Prior to upgrading, this action (one of the most commonly called in our application) averaged 225-250 ms.

Rails 3.0.4 Day 1

One our first day after upgrading, we found the same unmodified action averaging 480ms. Not cool.

Thus began the investigative project. Since New Relic was not working with Rails 3 views this week (seriously. that’s a whole different story), I (sigh) headed into the production logs, which I was happy to discover actually broke out execution times by partial. But there seemed to be an annoyingly inconsistent blip every time we called this action, where one of the partials (which varied from action to action) would have would have something like 250-300 ms allocated to it.

I casually mentioned this annoyance to Mr. Awesome (aka Jordan), who speculated that it could have something to do with garbage collection. I’d heard of Ruby GC issues from time to time in the past, but never paid them much mind since I assumed that, since we were already using Ruby Enterprise Edition, the defaults would likely be fine enough. But given my lack of other options, I decided to start the investigation. That’s when I discovered this document from those otherworldly documenters at Phusion, describing the memory settings that “Twitter uses” (quoted because it is probably years old) to run their app. Running low on alternatives, I gave it a shot. Here were our results:

304 Twitter mem settings

New average time: 280ms. Now that is change we can believe in! Compared with the default REE, we were running more than 40% faster, practically back to our 2.2 levels. (Bored of reading this post and want to go implement these changes immediately yourself? This is a great blog describing how. Thanks, random internet dude with broken commenting system!)

That was good. But it inspired Jordan to start tracking our garbage collection time from directly within New Relic (I don’t have a link to help ya there, but Google it — I assure you it’s possible, and awesome), and we discovered that even with these changes, we were still spending a good 25-30% of our time collecting garbage in our app (an improvement over the 50-60% from when we initially launched, but still). I wondered if we could get rid of GC altogether by pushing our garbage collection to happen between requests rather than during them?

Because every director will tell you that audiences love a good cliffhanger, I’ll leave that question for the reader to consider. Hint: after exploring the possibility, our action is now faster in Rails 3 than it had been in Rails 2. It’s all about the garbage, baby.

Rails 3 Unit and Integration Tests Slow: So Fix It

Another topic for which there is no shortage of Google results, but none that have really helped us to figure out why it takes upwards of three minutes for our tests to start. Finally reached my breaking point today and decided to track down what was behind the painful slowness of our test invocation.

The answer, for us, was the time it takes to purge and re-load the database when tests were starting. To figure this out, I simply ran

rake test --trace

And observed as we sat for two minutes on the db:schema:load. Ouch.

The good news is that, since we don’t use fixtures (chill runs down spine at the thought), there is really no need for us to purge our test DB every time we want to invoke tests. So, I decided to hack together a patch to allow tests to begin without the usual purge/load dog and pony show that goes with starting tests. If that’s the sort of thing that you’d be into, here’s the code you need to make it happen (in Rails 3, not sure how this might vary for Rails 2):

Rake::TaskManager.class_eval do
  def remove_task(task_name)


namespace :db do
  namespace :test do
    # Re-creating the DB every time we run tests sux...
    task :load do

Basically, the first bit is to undefined the existing “db:test:load” method, and the last part redefines db:test:load to do nothing. Add this as a mixin in your config/initializers directory and you should be golden.

If you do want to re-create your test database on occasion, you can still do that by running

  rake db:test:purge RAILS_ENV=test
  rake db:schema:load RAILS_ENV=test

Chances are that the RAILS_ENV isn’t even necessary there, but I don’t really feel like testing whether or not it deletes my main database atm.

Using this, our test start time dropped from about 3 minutes to 10 seconds. And that’s change that we can believe in.