Apache Pinot-focused StarTree raises $24M Series A

Company focused on LinkedIn-pedigreed OLAP analytics technology raises $24M Series A on top of a $4M seed round. Money will go toward completing its service build-out and growing adoption of the underlying open source tech.
Written by Andrew Brust, Contributor

New analytics pure play StarTree is today announcing it has raised $24M in a Series A funding round. StarTree is focused on operationalizing Apache Pinot (incubating), an analytics engine which began life as an internal project at LinkedIn in 2015. Including its seed funding round, StarTree has now raised $28M in total. The series A round was led by Bain Capital Ventures and GGV Capital, with investment from existing investor CRV.

Not your father's OLAP

ZDNet spoke with StarTree co-founder Kishore Gopalakrishna, who explained that Pinot is focused on dimensional OLAP (online analytical processing) queries, though the technology is not based on OLAP cubes of old. Unlike the classic technology, which relied upon pre-calculated aggregations for speed, Pinot uses a combination of column store technology and a variety of indexing techniques. The indexes are created automatically, so users need not worry about designing or tuning them, but can provide manual index designs if they so desire.

Gopalakrishna also explained that Pinot works very well with Apache Kafka (a technology also created at LinkedIn) and makes it much easier for technologists to work with the real-time, streaming data that is Kafka's bread and butter. StarTree is focused on creating an enterprise-grade distribution of Pinot and offering it as a service. The skill set required to implement Pinot on-premises is not trivial according to Gopalakrishna, giving the managed service a value proposition that is apparently quite high.

Adoption is a feature

Gopalakrishna said the Series A funding will be used for completion of initial development of the StarTree service and for advancing Pinot adoption overall -- especially in the use of customer-facing analytics. That adoption has grown by an order of magnitude over the last year, but given that meant an expansion of 100 active community members to 1000, growth of the Pinot ecosystem has a ways to go.

Is the market ready for yet another open source analytics engine? Some skepticism is in order. On the other hand, Gopalakrishna says that Pinot powers all of the analytics LinkedIn users see when reviewing profiles, and that it does all the work on the fly, with extremely low latency. Uber uses Pinot, too, to create dashboards for restaurant owners served by Uber Eats. Killer apps such as these may help Pinot, and StarTree. Meanwhile, analytics pros get to pursue another avenue of expertise.

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