Updated November 2021 Elasticsearch is a distributed search and analytics engine. It is built on top of Apache Lucene. Elasticsearch was first released in 2010 by the company now known as Elastic. It was originally completely open source, but recent license changes have limited its usage. More on that below. Elasticsearch is part of a … Continue reading Elasticsearch Basics: What it is, Licensing, Languages, and Getting Help
Updated April 2022 Boolean queries in Elasticsearch are a popular query type because of their versatility and ease of use. Boolean queries, or bool queries, find or match documents by using boolean clauses. For the vast majority of cases, the filtering clause will be used because it can be cached for faster search times. In … Continue reading How to Query Elasticsearch With Boolean Queries
Updated December 2021 Kibana Query Syntax When querying Elasticsearch in Kibana you can either use the traditional Lucene query syntax or the newer Kibana Query Language (KQL). If you are using Kibana 7.0 or later, Kibana Query Language is included as a default. In this article we provide the basics for both approaches and provide … Continue reading How to Query Elasticsearch in Kibana
Updated September 2021 Both Apache Solr and Elasticsearch are popular open source* search engines built on top of Lucene. This article is intended to help readers learn more about the technologies in relation to one another to guide technology decisions. * Check out this article for information about recent Elasticsearch licensing changes. Elasticsearch is no … Continue reading Solr vs Elasticsearch
Updated January 2021 An Index in Elasticsearch is used to both organize and distribute data within a cluster. In this post we will define both components of an Index and then outline how to create, add to, delete, and reindex Indicies in Elasticsearch. We will also touch on querying, but querying will be covered in … Continue reading How to Index Elasticsearch
Updated June 2022 Taking a break from Elasticsearch optimization posts to get back to the basics to define fundamental Elasticsearch concepts. Elasticsearch Definitions: A Primer for Elasticsearch Fundamentals Elasticsearch Node. An Elasticsearch node is a single Elasticsearch process, and the minimum number of nodes for a highly available Elasticsearch cluster is three. Continue reading about … Continue reading Elasticsearch Definitions
Updated April 2021 Optimizing Elasticsearch for shard size is an important component for achieving maximum performance from your cluster. To get started let’s review a few definitions that are an important part of the Elasticsearch jargon. If you are already familiar with Elasticsearch, you can continue straight to the next section. Defining Elasticsearch Jargon: Cluster, … Continue reading Elasticsearch Shards — Definitions, Sizes, Optimizations, and More
Updated April 2021 The way nodes are organized in an Elasticsearch cluster changes depending on the size of the cluster. For small, medium, and large Elasticsearch clusters there will be different approaches for optimization. Dattell’s team of engineers are expert at designing, optimizing, and maintaining Elasticsearch implementations and supporting technologies. Find our more about our … Continue reading Elasticsearch Optimization for Small, Medium, and Large Clusters
Monitoring Kafka cluster performance is crucial for diagnosing system issues and preventing future problems. We recommend using Elasticsearch for Kafka monitoring because Elasticsearch is free and highly versatile as a single source of truth throughout any organization.
Dattell’s engineers work one-on-one with companies to design, implement, manage, and improve their Elasticsearch deployments. Get answers to top questions about Elasticsearch consulting and managed services.
We broke down the thought process for choosing between AWS Elasticsearch and a custom Elasticsearch solution here to help you think through what will be right for you and your team.