You might not give much thought to your company’s data platform or data warehouse, 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 OpenSearch backend, they quickly realized five important facts.
What is AWS OpenSearch
AWS OpenSearch is a search and analytics service, based on OpenSearch, an open-source, distributed search and analytics suite derived from Elasticsearch. AWS OpenSearch lets you run and scale OpenSearch clusters without having to worry about managing, monitoring, and maintaining your infrastructure, or having to build in-depth expertise in operating OpenSearch clusters2.
Some of the benefits of AWS OpenSearch:
- It supports the latest versions of OpenSearch, as well as 19 versions of Elasticsearch, and provides visualization capabilities powered by OpenSearch Dashboards and Kibana.
- It offers a variety of features and integrations, such as machine learning, alerting, anomaly detection, SQL, trace analytics, and more.
- It provides high security and compliance, with features such as encryption, authentication, authorization, audit logging, and fine-grained access control.
- It enables cost-effective and scalable solutions, with options for hot, UltraWarm, and cold storage tiers, and cross-region replication.
Why is AWS OpenSearch good for embedded analytics?
It allows you to easily ingest, secure, search, aggregate, view, and analyze data for several use cases, such as log analytics, application monitoring, observability, and website search. You can also use SQL to query and visualize your data in OpenSearch Dashboards. AWS OpenSearch is designed to provide fast and reliable performance, as well as flexibility and customization, for your analytics needs.
How OpenSearch / ElasticSearch Can Save Money
1) There’s Virtually No Limit on Data Size
Even with databases spanning hundreds of millions of rows, OpenSearch was able to deliver millisecond response times that were far superior to anything their Oracle systems could ever hope to deliver.
2) OpenSearch Handles Both Structured and Unstructured Data
Their core data was structured, but 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 OpenSearch 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. Learn more about how OpenSearch OpenSearch can be used as a data warehouse.
3) Cost Savings
The third thing they soon realized were the cost savings. OpenSearch 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, scalable, feature-rich solution and is able to provide incredible savings versus traditional data platforms. See for yourself.
4) OpenSearch is Flexible
They were able to realize that OpenSearch is the perfect balance between the rigidity of SQL-based platforms and the flexible but chaotic nature of storage systems like Hadoop. OpenSearch sits comfortably in the middle, providing the best of worlds for analytic capabilities.
5) OpenSearch Can Be Deployed Anywhere
Lastly, OpenSearch was able to provide one final key component, the ability to deploy everywhere. OpenSearch 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 OpenSearch, 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.
Brian is the Head of Product Marketing at Qrvey, the leading provider of embedded analytics software for B2B SaaS companies. With over a decade of experience in the software industry, Brian has a deep understanding of the challenges and opportunities faced by product managers and developers when it comes to delivering data-driven experiences in SaaS applications. Brian shares his insights and expertise on topics related to embedded analytics, data visualization, and the role of analytics in product development.
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