Open Source Shifts to Software-as-a-Service

Tracking open source software in 2014, particularly around Big Data, showcased a shift towards Software-as-a-Service models. It makes sense. Since open source is free, there is a natural tendency for users to see how far that approach can go before spending money on software.
With SaaS, there is an immediate connection to a Service (it’s in the name of course), plus the natural connection that we usually pay for services.

Startups moving Open Source to SaaS

A number of startups have launched new offerings that point in the SaaS direction. Last year Rackspace acquired ObjectRocket which at the time provided MongoDB as a service, and has since expanded to add Redis as well.
Starting in the summer of 2014 Databricks launched their Spark-based Cloud Platform at the Spark Summit. Watch the video from the summit if you want more on the Databricks Cloud.
In August, MongoHQ (another MongoDB as a service provider) changed their name to Compose.io and added Elastic Search, built on top of Apache Lucene. Since then Compose.io had added support for RethinkDB and Redis, and offers deployments on AWS, Digital Ocean, SoftLayer, and GoGrid.
Not to be left out, Apache Cassandra as a service appeared in September 2014 when Instaclustr announced $2 million in funding including participation from DataStax, the dominant provider of Apache Cassandra solutions.
In October 2014, MongoDB announced enhancements to the MongoDB Management Service, a cloud service to manage MongoDB deployments. Press stories played on the explanation to declare MongoDB targeting a ‘massive’ revenue stream.

Mapping Software Categories

In the spirit of Peter Thiel, I drafted a 2x2 matrix to understand four categories of software:

• In-house Development
• Commercial Software
• Open Source
• SaaS

On the X axis I added Predilection to Pay Someone Else, which gets back to the introduction of this post that there is a not-so-natural disposition to pay for open source software, and there is a much more natural disposition to pay for services, including those that deliver software.
On the Y axis I added Ease of Adoption with the intent to loosely categorize the time, energy, and money spent up front to deploy software.
The trends among startups recently has been centered in the shift depicted by arrow 1. However, other migrations are in effect from the popularity of commercial SaaS offerings like Salesforce, Box, and Workday, along with the ongoing march of AWS cloud domination.

Finding the Center of Data

In the pre-cloud days, most folks could point to the data center which housed all the important company information. Today, that concept has vanished into multiple cloud computing providers and SaaS solutions.
The center is shifting outside the data center. Interconnecting software and applications has become more important than having them in a one place, and enabling flexibility, mobility, pay-as-you-go, and ease of adoption will only further the SaaS bandwagon.
Have favorite examples of the open source to SaaS shift? Add them in the comments or send to me on Twitter @garyorenstein.