Elastic customers have seen a 5% revenue improvement within three years, among other benefits. How? Using Elasticsearch, developers can ingest and connect various data sources to provide their companies, employees, customers, and/or public access to information and tune results for faster, more precise answers. Elasticsearch AI/ML powered search is designed to maximize performance and compute resources to deliver applications that can scale as businesses grow.

Generative artificial intelligence (GAI) is undoubtedly one of the biggest trends across industries in 2023. In a recent survey, almost two-thirds of executives believe generative AI will have a high or extremely high impact on their organization in the next three to five years. Executives anticipate spending the next 6–12 months focused on increasing their understanding of how generative AI works, evaluating internal capabilities, and investing in generative AI tools.

In a recent blog post, we discussed how ChatGPT and Elasticsearch® can work together to help manage proprietary data more effectively. By utilizing Elasticsearch's search capabilities and ChatGPT's contextual understanding, we demonstrated how the resulting outcomes can be improved. In this post, we discuss how users’ experience can be further enhanced with the addition of facets, filtering, and additional context.

If you’re looking for a short answer on OpenSearch vs Solr, here’s a flow chart: We normally recommend the one you (or your team) already know or the prefer because, for most projects, there’s not that much in it in terms of features. Both search engines are well supported and have strong communities behind them. That said, there are significant differences, too.

Elastic Enterprise Search 8.8 seamlessly bundles new Elastic developed semantic search capabilities with an expanding catalog of open code database and storage connectors. Additionally this release adds rich capabilities to measure and simplify adding features to your search application. These new capabilities allow customers to: Elastic Enterprise Search 8.8 is available now on Elastic Cloud — the only hosted Elasticsearch offering to include all of the new features in this latest release.

Elasticsearch is a search and analytics engine that allows for complex searches on large datasets of different types and formats. Elasticsearch mappings are the blueprints that define how data is indexed and searched to support these data-related features. Understanding how Elasticsearch mappings work is essential to an effective Elasticsearch deployment. In this article, we’ll explore the key concepts of Elasticsearch mappings and common Elasticsearch mapping pitfalls to avoid.

The Elasticsearch reindex API copies data from one index to another. You can use reindex to change the index mapping, copy data to another cluster, or copy only a subset of data to another index. For example, suppose you want to reindex all the data in index1 into index2. In that case, you run the following example in Kibana dev tools: In this article, we dive into some common issues solved by reindexing as well as troubleshooting issues with reindexing itself.

Starting the journey for Elasticsearch monitoring is crucial to get the right visibility and transparency over its behavior. Elasticsearch is the most used search and analytics engine. It provides both scalability and redundancy to provide a high-availability search. As of 2023, more than sixty thousand companies of all sizes and backgrounds are using it as their search solution to track a diverse range of data, like analytics, logging, or business information.