Elasticsearch Global BV is continuing its quest to build a business based upon open-source software with a bundle of products anchored by its Elasticsearch search engine and targeted at big data applications.

Elastic Stack 5.0 bands together a suite of products that were previously offered separately, including the Kibana visualization engine, Beats data shipper, Logstash log data manager and Elasticsearch for Apache Hadoop. The stack also includes proprietary extensions for security, alerts and monitoring. The entire suite is available as a free download or cloud service, with options for subscription-based support.

The company, which does business under the name Elastic, was co-founded five years ago by Shay Banon (@kimchy), the original developer of Elasticsearch. It’s seeking to court enterprise customers who want a single point of accountability for a suite of related open-source software. The company says its namesake search engine has been downloaded more than 75 million times.

Elastic Stack is intended to address many of the interoperability issues that plague open-source projects that encompass multiple tools. “We’ve taken time to make sure the experience is completely streamlined,” Banon said in an interview. “We want to reduce the time to success for log analysis to five minutes.”

Log analysis is just one of the applications that have sprouted up as users have discovered new ways to apply search. Most people think of search engines as simply quick ways to find information, but in an enterprise context they can be used for tasks like combing through large amounts of semi-structured information to identify patterns and anomalies. Banon said about 30 percent of Elasticsearch users are doing some kind of log analysis, which is useful in security forensics and fraud detection. “We’re educating our user base that this is more than just search,” he said.

Proprietary extensions

In adding proprietary extensions to open-source code, Elastic is walking a fine line between being an open source provider and a commercial software company. Pure-play open-source businesses such as Hortonworks Inc. have struggled to find a profitable growth path solely through paid support and professional services. Elastic’s paid subscription model is also support-based, but subscribers get access to proprietary extensions.

“If you’re only selling support for open source, your goal is be to provide the best support possible, but if you do that you’re going to eventually work yourself out of a job because customers become self-sufficient ,” Banon said. “I’m proud of saying we have commercial intellectual property on top of open source.“

The company is doing that through an extension model based on published application program interfaces and built into its open-source distributions. Developers can use the APIs to add their own extensions, and Elastic provides a library of its own. They include a product that collects and stores Elasticsearch log data for display in Kibana as well as a security module with node-to-node encryption.

Search engines have characteristics that make them distinctly useful in big data scenarios where relational databases would be impractical, Banon said. He cited the example of a quest to find all tweets that mentioned Donald Trump in California over the past 20 days, have more than 500 retweets and a set of positive attributes, and displaying the result as a heat map trend over time. “You would never ask a relational database to index that many fields, but its very easy to do with Elasticsearch,” he said.

The company doesn’t publish pricing for its on-premise subscription service, but prices its cloud service beginning at $45 per month.

Kibana image courtesy of Elastic