The central role of the open-source movement in analytics rose back to the surface last week after LinkedIn Inc. released another one of its internally-developed data crunching technologies under a free license to help promote emerging use cases. And in particular, performing real-time business intelligence at the kind of scale where the traditional databases typically used for the task fall short.
Pinot, as the project is known, currently stores over 100 billion records in support of more than 30 of the professional social network’s most important features, including the tracking capability that allows users to see who viewed their profiles and the analytic functionality provided to advertisers. That scalability could go a long way for organizations with needs likewise exceeding the capacity of existing options on the market.
But what makes Pinot not only appealing but also practical for the traditional enterprise is a relatively simple interface that allows users without specialized skills to interact with the data stored inside, the same pitch behind another open-source analytics project that made headlines last week. The difference is that Pachyderm is geared towards developers rather than business users.
The startup behind the software announced the completion of a $2 million seed round from Foundation Capital and a number of other-high profile investors on Thursday to help fuel the development of the free Hadoop implementation, which promises to simplify batch analytics. Pachyderm accomplishes that by automatically distributing workloads across preconfigured containers and adjusting the size of the cluster as needed from there.
The platform scans for patterns in consumers’ activity to try and predict what products they’re likely to buy next, an approach that is finding success with PayPal Inc. and VMware Inc. and other big-name customers. The new capital will go towards developing new value-added to help marketers take even better advantage of that functionality.
