2011 PaaS Predictions: Winners and Losers

This past year has been an interesting one in the cloud space, and particularly for Platform-as-a-Service. While PaaS has certainly increased in popularity over the past year, I think it is still at the bottom of what is going to be a hockey-stick like growth curve. That obviously means that 2011 is going to be an even bigger year for PaaS. Given that is the case I wanted to put down my predictions for what I think it going to happen in the space over the next year.


Heroku’s $212 million dollar acquisition by Salesforce was probably the biggest news of the year in the platform space. Not only is it a huge win for one of the most popular platforms, it is also a validation of the fact that the space is going to be huge. However, any time a small agile start up gets bought up by a giant corporation there are obvious concerns that they will lose their agility and get out of touch with the customers who made them successful. Given what I’ve seen from the Heroku guys so far I think they have a strong enough vision and understanding of their customers that they will be able to fend off the temptations of SF execs to meddle with their newly acquired toy.

I also suspect that we will see Heroku start getting a little more enterprisey in their offering over the next year. Unfortunately I don’t think they will see a lot of uptake since most enterprises move slower than molasses on a cold day.
Overall: OK

Google AppEngine

In addition to having incredibly liberal quotas, AppEngine has long been one of the most feature rich platforms available. Yet, there have been two main issues which really held back what would have otherwise been incredible growth, performance and datastore.
One of the most common complaints I have heard from developers using AppEngine is poor performance. This issue came to a boiling point earlier in the year when datastore latencies got so bad that Google stopped charging for Datastore CPU usage. The datastore issues were subsequently resolved and Google was able to deliver a substantially faster datastore API. Following this issue I think over the next year Google will start drilling down on other performance issues and deliver a much more performant and stable platform.

The other main point of friction for datastore has been the fact that it relies on a NoSQL like data model. While NoSQL is all the hotness right now, the vast majority of developers are still not comfortable using non-relational data models. That is why the announcement of a SQL database as part of AppEngine for Business came with much celebration. While it is still in private beta I would suspect that we will see it publicly released this year which will bring in a new wave of customers ready to take advantage of the large quotas and familiar SQL tools.
Overall: Very good


While AppEngine is a great platform for Python applications there has been pent up demand for a Python/Django version of Heroku. New startup Djangy looks to be the first viable attempt at filling that gap. Looking at their documentation they seem to have taken the “Heroku for Python” manta very seriously, and that is a good thing. While Djangy is currently in private beta I’m guessing that they will be gearing up for public launch in the next 3-6 months. After that I think we will see quite a few Pythonistas migrate over to Djangy so they can get back to using the tools they are familiar with (Full Django + SQL).
Overall: Very good


DotCloud is a new Y-Combinator startup which aims to bring more flexibility to the platform space. Rather than a platform being married to a single language and database technology they aim to allow you to mix-and-match many languages (Ruby, PHP, Java, Javascript) and database technologies (MySQL, PostGREs, Redis, MongoDB). It is the choose your own adventure version of cloud platforms. Unfortunately I think using Dot Cloud will be just that, an adventure, and not the good kind.

As I discussed in my previous blog post, fragmentation is a huge issue for platform providers. I was discussing fragmentation within the context of a single language but the problem absolutely explodes when you start mixing in multiple languages with multiple databases. Consider the fact that even Google, a company with a tremendous amount of technical resources, only supports two languages and one database. While their vision is great one, I think they are going to run into some issues. In particular, they are going to reach a very unfortunate fork in the road. One path will be to only do barebones support for each language/database and risk frustrating customers with their lack of options. The alternative path will be to provide more in-depth support for each component and have to live the burden of regression testing the myriad of combinations possible, destroying their agility. Frustration seems inevitable either way.
Overall: Poor


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