Mortar launched in 2012 and was initially focused on providing a simple way to run Hadoop jobs in the Amazon Web Services cloud using languages such as Python and Pig. The company eventually launched an open source project to house a lot of its work, including some around building reusable frameworks for common big data applications such as recommendation engines. Recently, Mortar added support for numerous new open source technologies, including Spotify’s Luigi pipeline tool and Apache Spark.
The company had raised $3.2 million in equity and debt financing, including a $1.8 million seed round, according to Crunchbase.
Datadog will be closing down Mortar’s service, and the Mortar team and platform will work inside Datadog analyzing operational data that can be turned into additional analytics for users. Datadog was already a Mortar user. In fact, Chief Product Officer Amit Agarwal said in an interview about the acquisition, “Mortar was our Hadoop, for the most part . . . We already had a common law relationship.”
Datadog has raised more than $50 million in venture capital since launching in 2010, including a recently announced $31 million round.
Mortar Co-founder and CEO K Young said his company is “taking a lot of care” right now to ensure users have a smooth transition away from the hosted Mortar platform. Part of that process involves releasing a lot more components into the open source repository, he said.
Mortar Data had a solid idea and was one of the first to market with a cloud-based Hadoop service, but apparently the company’s approach didn’t resonate with consumers. Or perhaps its business model didn’t scale. I used to compare Mortar to Infochimps and Continuuity, the former of was acquired by CSC in 2013 while trying to raise money and the latter of which changed its name to Cask and open sourced its technology.
Even if you’re focused on data scientists or developers, it’s difficult to compete in the world of big data infrastructure without very deep pockets. Similar startups that have launched since Mortar, including Altiscale and Qubole, raised significantly more capital and appear to be doing decent business. Databricks, the unofficial corporate arm of the Apache Spark project, has also raised boatloads of capital and is banking on a cloud computing service, as well.
That’s not to mention the difficulty of selling users on your service when the cloud providers themselves — particularly [company]Amazon[/company], [company]Microsoft[/company] and [company]Google[/company] — continue rolling out bigger, cheaper and fast data services.
We’ll be talking more about the still-emerging big data market at our Structure Data conference next month in New York. Executives from the world’s leading big data software vendors and cloud providers, as well as many cutting-edge users, will be discussing where the business is headed and what technologies are the next big things.