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Five Facts About Elasticsearch That Can Save Big Money

You might not give much thought to your company’s data platform, but what you don’t know could be costing you potentially millions of dollars! In this article, I’ll discuss how one of Qrvey’s oldest clients, a large healthcare software provider, took advantage of just five attributes of our platform that translated into huge savings.

The client has been deploying custom software solutions into hospitals built on legacy Oracle databases for many years. Their reporting and analytic solution of choice had been Tableau. However after beginning to migrate their data into Qrvey, which includes a modern Elasticsearch backend, they quickly realized five important facts.

First, there’s virtually no limit on data size. Even with databases spanning hundreds of millions of rows, Elasticsearch was able to deliver millisecond response times that were far superior to anything their Oracle systems could ever hope to deliver.

Second, while their core data was structured, they also had tons of loosely structured data that included nested and hierarchical data. None of this data could  provide the full picture without being linked to each other. Thus, entire troves of unstructured, text-based data had been completely ignored and was never considered for analysis. But Elasticsearch was able to ingest and link their structured, semi- and unstructured data with ease, giving them a complete picture of their data for the first time.

The third thing they soon realized were the cost savings. Elasticsearch is a modern, open-source database that didn’t even exist as a viable product in the marketplace just five years ago. But now, it is a powerful, scaleable, feature rich solution and is   able to provide incredible savings versus traditional data platforms.

Fourth, they were able to realize that Elasticsearch is the perfect balance between the rigidity of SQL-based platforms and the flexible but chaotic nature of storage systems like Hadoop. Elasticsearch sits comfortably in the middle, providing the best of worlds for analytic capabilities.

Lastly, Elasticsearch was able to provide one final key component, the ability to deploy everywhere. Elasticsearch can be installed on everything from a small, local server to a variety of public and private cloud options. In this case, the client was able to begin loading their data and testing in a local environment in just a day, before ultimately moving to their own private cloud, where they maintain maximum control and security along with maximum flexibility and performance.

Qrvey is the only self-service analytic provider that’s built on Elasticsearch, offering no-code analytic applications plus the ability to easily connect to any datasource using Data Router, our high-performance data ingest and transformation engine.