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Summary:

Elasticsearch, the company behind a very popular open source suite for indexing, searching and visualizing JSON documents, has raised a $70 million series C round of venture capital. Just more than two years since being founded, the company has raised $104 million.

Elasticsearch CTO Shay Banon.
photo: Elasticsearch

Elasticsearch, the company behind the popular open source search engine, has raised a $70 million series C round of venture capital from New Enterprise Associates. Existing investors Benchmark Capital and Index Ventures also participated. The company has now raised $104 million since launching in early 2012.

That’s a significant amount of money for such a young company, and an open source one at that, but it goes to show that users can matter in enterprise IT just as much as they do in the consumer world. When we profiled Elasticsearch in January, the open source project for quickly indexing and searching JSON files — which also includes a log-management tool called Logstash and a visualization tool called Kibana — had surpassed 6 million downloads and the company had just launched its first commercial product, a monitoring tool called Marvel.

The company now claims more than 8 million downloads and continues adding large companies to its list of paying customers that includes Comcast, eBay, Facebook, Mayo Clinic and quite a few more household names. It’s becoming mission-critical to a lot of these companies, CEO Steven Schuurman said, to the point where some big brand names would take a “meaningful hit” if their Elasticsearch services went down. And, he added, “When a product becomes mission-critical, it becomes monetizable.”

Elasticsearch CTO Shay Banon.

Elasticsearch CTO Shay Banon.

Some of those customers, including Booking.com, are using Elasticsearch for their front-end search functionality, co-founder, CTO and project creator Shay Banon said. In some other cases, the technology made its way into IT budgets because business personnel saw some the analysis developers were able to do and some of the graphs they created using Kibana, and they wanted more. One large bank uses Elasticsearch so it has real-time visibility into the access logs it stores in Hadoop as part of a fraud-detection process.

Banon said it’s relatively easy to add new users because of how simple it is to get started. There are no long proof-of-concept projects; in fact, most users just get started experimenting with a day or a week worth of log files. “It’s much easier to find a single server than to try to find 50,” he said.

Although Marvel is only four months old and is free until users begin running it in production environments, it’s also starting to contribute to the bottom line. “People like to take their time to really evaluate the product,” CEO Schuurman acknowledged, but many are ultimately buying licenses.

A sample Kibana visualization.

A sample Kibana visualization.

But more paying users also means more responsibility to support them, he added, which is why the company decided it needed to raise more money. The company has about 90 employees right now and Schuurman expects it will double its headcount in the next year. It just hired its first employee in Japan, which is home to one of the fastest-growing Elasticsearch user groups. It’s also picking up popularity in China and South Korea, and throughout Europe.

“The last 6 to 12 months have been phenomenal from an entrepreneurial perspective,” Schuurman said.

That’s probably a fair statement. By way of comparison, popular open source database startup MongoDB as been around since 2007 and was only claiming 5 million downloads as of October 2013. Elasticsearch has raised more capital (very much on its own terms, Schuurman pointed out) than either MongoDB or Hadoop startups Cloudera and Hortonworks had at this point in their corporate lives.

ES funding

  1. Reblogged this on Invest Your Time.

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  2. “the open source project for quickly indexing and searchingJSON files”
    Actually it is system that handles clustering, realtime access of, distributed and etc Lucene Indexes. It makes it easy so you can use JSON to communicate with it (vs the raw Lucene API or XML). It does not store JSON files (files are things you write to disc). It might store JSON documents ;). The key point to ElasticSearch is not JSON. If you have ever used raw Lucene (dont get me wrong, Lucene is awesome) you will see the value of ElasticSearch

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