In today’s data-centric world where buzzwords like big data, machine learning, and data analytics are littered across every tech related blog, Elasticsearch is attracting increasing attention as the go to enterprise level search engine. However, its abilities to provide lightning fast results in a scalable package coupled with the data analytics capabilities are making it increasingly popular in the data community where its performance in real-world applications makes it the go-to solution for agile data analytics.

Before discussing its applications, let’s delve into the features that make it so favorable for the real world scenarios. Elasticsearch is essentially built upon the very powerful, but inherently complicated, Apache Lucene search engine library. Rather than searching text directly, it creates an index much like the one you would find at the end of a textbook and searches through it. This gives it the capability to provide near-real-time results, making it favorable for instant searches as well. Moreover, compared to conventional SQL databases, Elasticsearch offers the ability to work on loosely structured raw data (schema-less) making it highly relevant in today’s world where data is derived from a wide variety of sources and has varying structure.

Fast results and schema-less design aside, Elasticsearch comes with a variety of tools and plugins that take its abilities beyond those of your typical search engine. Coupling it with the Logstash tool, you can easily mine all the data in your structures to observe trends and anomalies. For more sophisticated business intelligence requirements, Kibana can be used to create complex queries as well as create custom dashboards to visualize your data effectively. Moreover, being open source, there is a wide variety of clients available to allow you to utilize Elasticsearch in your programming language of choice ranging from old favorites like Java to higher level languages like Python.

These features provide Elasticsearch with a unique flexibility and use cases in seemingly unlikely applications. In addition to traditional search scenarios such as users searching through websites like Github or applications like Netflix, it is also the analytics tool of choice for NASA. Elasticsearch is being used to analyze data from the Curiosity Rover on Mars allowing scientists to observe trends and anomalies far quicker than previously possible, giving them additional agility. Closer to Earth, it was also used by NASA in the Soil Moisture Active Packing program. The performance advantage offered by Elasticsearch has led it to be a part of NASA’s operational data system for data analysis.

Elasticsearch also found home at another unlikely place: Fender, the world famous guitar brand. Although it seems an unlikely place for a search engine, Elasticsearch provides the company the ability to not only search through its network of dealers but also provide insights and analytics to ensure their operation runs efficiently and smoothly and to identify anomalies quickly.

NoSchoolViolence.org went a step further and used Elasticsearch for a far nobler cause. They created Lantern, an analytics tool that tries to find trends and relations between observable behavior patterns and occurrences of violence, particularly in schools. Plowing through a variety of unorganized data, ranging from police records and academic journals, the schema-free design of Elasticseach proved to be a savior for the project allowing users to stop instances of violence from occurring proactively.

Another impressive use case of Elasticsearch was at Expedia, a popular travel website that deals with massive amounts of data on a daily basis. The business intelligence capabilities made it extremely easy for their teams to keep track of performance while the scalability means they can deal with the 1TB of data generated daily with no degradation in performance.

All in all, one would feel that the “search” in Elasticsearch does not do justice to its amazing capabilities. Its use cases ranging from analyzing data from Mars to allowing behavioral scientists to delve through data to preemptively stop violence from occurring pay homage to its flexibility and usability. With the requirement for data-focused applications in a variety of industries growing stronger, Elasticsearch proves to be a flexible and agile one stop solution no matter what the requirement.