Big Data Search Tool Elasticsearch Gets $24M in Series B Funding


Amsterdam-based Big Data startup Elasticsearch, which operates the real-time search and data analytics open-source project of the same name, has just secured a handsome $24 million in series B funding, which it says it plans to use to make its platform more user-friendly.

The bulk of these funds were provided by Mike Volpi of Index Futures, with smaller contributions coming from SV Angel and Benchmark Capital. The investment, which means that the startup has secured $34 million funding in total, once again emphasizes the demand from small and medium-sized businesses for free and simple-to-perform Big Data analytics.

Elasticsearch is an unusual startup that makes money by holding training courses where it teaches people how to use its Big Data search tools, and it also raises cash by helping companies solve problems through its support subscriptions. The open-source project was launched in 2010 by founder Shay Banon, who developed it in his spare time. Six months ago, Banon brought Steven Schuurman onboard as CEO and launched Elasticsearch as a fully-fledged company.

Elasticsearch’s tools can make fast work of Big Data problems, providing enterprises with a quick and easy way to analyze petabytes of information in just seconds. By searching through millions of petabytes of unstructured data and documents in the blink of an eye, Elasticsearch helps companies to glean intelligent insights that can immediately be applied to make actionable decisions in something close to real-time – and what’s more, it’s completely, 100% free to use.

Since the project’s launch Elasticsearch has been downloaded more than 1.5 million times, and has now reached a rate of about 200,000 new downloads per month, according to Banon. One of its most prestigious users is Foursquare, which says that it can handle tens of millions of daily searches from more than 50 million locations each day, returning results in real-time.

Banon explains that search has evolved massively from where it was ten years ago, and that today’s tool’s must use a combination of free text search, structured search and analytics in order to deliver the most applicable results. When it comes to enterprise users, there is often a need to search through massive volumes of Big Data, and this is where Elasticsearch stands out, helping companies to effectively manage all of these functions, and do so more efficiently than is possible with other systems.

Elasticsearch hopes to expand its user base by making its software more user-friendly, with the main goal being to develop a shorter learning curve for new users. In addition, Banon says that he wants to boost the tool’s reliability and develop a deeper documentation library – an admission that Elasticsearch is perhaps beginning to experience problems related to scale. Nevertheless, with $24 million now safely banked, it should be able to weather these growing pains easily enough.