OpenSearch is an open-source search and analytics suite. Developers build solutions for search, data observability, data ingestion and more using OpenSearch. Another popular use case is log analytics. You take the logs from applications, servers and network elements, feed them into OpenSearch, and use the rich search and visualisation functionality to identify issues.

The latest release of Elastic Enterprise Search introduces a suite of new features and capabilities for building world-class search experiences for your mission-critical applications, websites, online stores, or anything in-between: With this release, building search experiences for your ecommerce retail site, enhancing your employees’ ability to access relevant HR documentation, or building a custom application to quickly draw analytic insights can draw on the power of using the trained model of

Creating personalized search experiences can be challenging. In this post, we’ll demystify the steps to get started, so you can prioritize search results according to user profiles, offer relevant recommendations, and accelerate workflows. But before we get to that, let’s address why personalized search matters.

In this article, we'll explore the concepts of variants and SKUs in ecommerce, and how to best handle these when modeling data for your ecommerce search experiences. We're optimizing our models using Elastic Enterprise Search.

Elastic continues to help everyone find what they need faster with Elastic Enterprise Search, a comprehensive solution for building search-powered applications. Elastic Enterprise Search elevates relevance and precision at scale with a new combination of traditional and machine learning-assisted techniques.

Some time ago, AWS forked ElasticSearch, the most popular search engine on the planet. They had some struggles with the maintainer of ElasticSearch and decided it was time to part ways. So, with OpenSearch, there is now a new kid in town. Well, not new, but at least some kind of alternative.

OK, so you want to sort your documents by something that can’t be implemented with Solr’s built-in functions. This calls for a custom function, which you can implement through your own ValueSourceParser. To address the elephant in the room, Elasticsearch and OpenSearch have script sorting. This is easier to implement, but not as close to Lucene. Though of course you can use a native script as well.

In Enterprise Search 8.4, hybrid ranking for vector similarity is now available from the main querying endpoint, commonly known as the _search Elasticsearch endpoint. Introduced as a standalone query endpoint in 8.0, vector querying functionality (specifically, kNN vector similarity) greatly simplifies and accelerates the process of crafting and issuing queries that leverage the native vector querying capabilities of Elasticsearch along with the tried-and-tested traditional scoring algorithms.