You’re hot, or not: why Elasticsearch raised $ 24 million just 3 months after a $ 10 million round

Yesterday, Elasticsearch announced a $ 24 million Series B round led by Mike Volpi of Index Ventures (San Francisco office), who will also take a board seat. The round includes contributions from existing investor Benchmark Capital and new investor SV Angel, who was an early Google investor too.

The announcement of the financing is a bit unexpected, as it comes on the heels of a $ 10 million Series A round in November 2012, which surely makes Elasticsearch one of the hottest startups in Europe at this moment.

Elasticsearch is a search engine for big data exploration, initially developed by Israeli born Shay Banon and released in 2010. While the solution is open source, Elasticsearch makes money by offering support, training and consultancy.

Here’s the introductory video by Banon from 2010:

It’s a bit technical, so fortunately, there’s also an interview available with founder Shay Banon. In it, he explains that he came to Europe because of his wife’s cooking classes (aw, sweet!). And that’s also why he started developing killer search tools, apparently: because he wanted to make a nifty, on stop tool for his wife to find all her cooking information.

That eventually evolved into Elasticsearch, which is capable of handling massive amounts of recipes:

Elasticsearch makes data exploration easy. Users and developers want valuable information from their data regardless of the form. While elasticsearch does free-text search very well, you also want structured search, analytics, aggregations, facets over the data, and more. We tie all these together nicely. 

For example, let’s say you are indexing a social string from Twitter like a lot of our customers do. You can easily set it up and ask questions like, “find all the tweets about the president.” This is a free-text search over a bunch of tweets.

Then you can say, “Find all the tweets about the president when tweeted from Idaho in the past month.” We sprinkle a bit more structure here by adding the location and time period. Then, we can ask it do the same thing, but break it down into number of tweets per day to see a trend over time.

So, we end up with a metric and several dimensions to show something of value.  After the initial query is set up, we can easily change the name of the president to any other person, and elasticsearch reflects the result—set in real-time. Then, we can change from a person to a topic like “flu epidemic,” and the result-set is reflected in real-time again.

For developers, its very powerful how easy data exploration becomes with elasticsearch. [Source]

Apparently, developers do love it. Elasticsearch says the search engine was downloaded a total of 2 million times, or 200 000 downloads per month lately. The Elasticsearch technology is used by huge web based organizations like Path, Mozilla, Soundcloud, StumbleUpon and Klout. Mike Volpi of Index: “We haven’t seen momentum like this for an open source project in quite some time.”

But why is it raising $ 24 million after it had already received $ 10 million four months ago?

Steven Schuurman, CEO of ElasticSearch, says on the company’s blog that a Series B wasn’t planned so soon. “In fact, we were still recovering from our previous fund raising adventure.” But, he says, the interest in investing in ElasticSearch was so great that the team started brainstorming about what it could do with new financing.

“Raising a Series B allows us to execute faster on our growth plans for the company and thereby do a better job at serving our rapidly growing customer base on both sides of the Atlantic, in the US and Europe. The driver of this growth is the rapid evolution of search itself.”

Search itself has changed over the last 12 months, says Schuurman, not only because search technology has become more powerful, but also because data volume has exploded. And it’s mostly not of the neatly structured kind: it comes in a variety of unstructured formats, in different places. On top of that, users expect real time analysis of their data. Says Schuurman: search is becoming the go to tool to explore massive amounts of data, rather than analytics solutions.

Here’s a few uses from an interview with founder Shay Banon“One of the coolest implementations is an email archiving company. They put a petabyte of data into elasticsearch. Then, they do unstructured search. This is interesting because it handles such large, distributed, big data problems.”

There is another company that stores and indexes all the download events of their online property - billions. They set up elasticsearch like a version of Google Analytics for their users. Their users can see download sources, usage patterns, histograms, trends, money made, geo-based filtering, and more.” 

“Path uses us to index moments. This is a lot of data. This is social graph search—search within my friend’s moments. Soundcloud is another one—when you search there, you can explore music by a variety of filters. 

Elasticsearch says it wants to use the money to make its solution stabler, improve its documentation, hire top talent and take Elasticsearch global. Sounds like they won’t get bored anytime soon. 

[Elasticsearch, Index Ventures,][photo: Arcturus Aldebaran, Flickr]

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About the author

Raf Weverbergh

Editor of whiteboard. Raf Weverbergh was a magazine journalist whose work appeared in magazines like Rolling Stone, Playboy, Mail on Sunday, Publico and South China Morning Post. He is the co-founder of FINN, a corporate communications agency where he advises startups and multinationals on their PR and Mustr, the easiest media database for PR professionals. You can contact him on Twitter, Linkedin or Skype (rafweverbergh).

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