Last week, we announced our $1.8 million fundraising. For those of you who follow big data startups, our blog post probably felt…underwhelming. Startups typically come out and make a huge publicity splash, jam-packed with buzzwords and vision galore. While we feel very fortunate to have what we need to help us grow, we know that VC funding is merely a means, and not an end.
But now you get to see us get really excited, because Mortar’s Hadoop PaaS and open source framework for big data is now publicly available. This means if you want to try it, you can activate your trial right now on our site without having to talk to anyone (unless you want to!).
You can get started on Mortar using Web Projects (using Mortar entirely online through the browser) or Git Projects (using Mortar locally on your own machine with the Mortar development framework). You can see more info about both here.
All trial accounts come with our full Hadoop PaaS, unlimited use of the Mortar framework, our site, and dev tools, and 10 free Hadoop node-hours. (You can get another 15 free node-hours per month and additional support at no cost by simply adding your credit card to the account.)
Where we started…
Our team has been banging our heads against big data for a long time. We’ve felt the pain of cumbersome ETL systems and other tools, and we were so excited about the potential of Hadoop. However when we started using it, we quickly realized it was really only accessible to large companies with deep pockets and big teams, and even then it took a VERY long time to get from “Hey, we want to use Hadoop!” to “Sweet! We’re using Hadoop!”
Our first iteration of Mortar was a browser-based version that made it easy to write jobs on our Hadoop PaaS using Apache Pig and Python. It was a great way for us (and our users) to get started quickly, but we always had a bigger vision, which we’re just now bringing to the public.
…and what’s new.
Mortar is an open source, code-based platform for big data. As a company, our Hadoop PaaS hosts and executes Mortar projects as a service. We’ve partnered with Amazon Web Services and built Mortar entirely on AWS, backed by their Elastic MapReduce offering.
You use Mortar by writing a combination of Pig (which is like SQL) and real Python. Historically, Hadoop has only worked with Jython, but the data science community told us over and over how deeply they depended on libraries like NumPy, SciPy, and NLTK. They were dying to use Hadoop, but they were being forced to choose between one set of tools or another. We wanted to fix this, so we made Hadoop and Python play nice together.
Our key focuses in building Mortar’s Hadoop PaaS are:
- Ease of use – engineers and data scientists can get started quickly using the tools they love, without training
- Collaboration – share/repeat/maintain your code using Git or other revision control
- Open source – customers should never be locked in
- Convention over configuration – do automated testing, find errors quickly
- Removing all non-core elements of building data pipelines – you shouldn’t waste time worrying about infrastructure and operations
Does it work for you?
I could write at length about how Mortar works, but you’re better off seeing it in action. Of course, the easiest way to really know if any software works for you is to try it for yourself. So if you want to do ETL, natural language processing, aggregations, machine learning, regression analysis, or some other big data analysis, you can try Mortar free.