Hosted Elasticsearch Service
Launch our supported, fully-managed, RESTful search
application instantly.
Scale up or down and pay as you go.
Powering Production Elasticsearch
Around the World
- Jib Jab
- Doordash
- 99Designs
- Roadtrippers
- Jelly
- Class Dojo
- Paysimple
- DigitasLBi
- Drizly
Free 24/7 support and maintenance for every customer
With Qbox, you can count on your clusters being up when you need them. You're fully backed with a SLA, a dedicated support team, and fully managed upgrades and migrations.
-
Fully managed upgrades and migrations
Upgrading to the newest Elasticsearch version has never been so easy. Our support team will work with you and follow up to make sure there are no issues with your cluster upgrade.
-
Automatic backups and simple restore
Have an issue and need to roll back? We're here to help. Qbox will work with you to quickly restore your data with minimal downtime.
-
Add or remove plugins on demand
Want to add the newest plugin on the block to your existing Elasticsearch cluster? With Qbox, it's as easy as sending a ticket to our support team. We'll take care of the rest.
Available on multiple cloud platforms in over 47 regions
Qbox is the only hosted Elasticsearch provider that allows you to choose both the location and the cloud platform of your cluster, which lowers response times significantly.
Infinitely Scalable
Launch a 1-node Elasticsearch cluster for testing and then scale to a 10-node production cluster with ease.
Unrestricted API
Whether it’s 10 thousand or 10 billion documents you need to index, we’ve got it covered.
VPC Peering
Increase your security and throughput with VPC peering. Available on clusters on the AWS platform.
Kibana, Logstash, and Elasticsearch. Get the ELK stack, a suite of powerful search analytics for your cluster.
Hook your cluster into the ELK stack to get detailed Kibana and Logstash analytics. Let our expert support team help design your ideal ELK Stack infrastructure.
Read more about the ELK StackElasticsearch News & Tutorials
Learn more about Qbox Elasticsearch and how to get the most out of shards, aggregations, and more.
-
A Deep Dive into Significant Terms and Significant Text Bucket Aggregations in Elasticsearch
In this article, we'll continue our overview of Elasticsearch bucket aggregations, focusing on significant terms and significant text aggregations. These aggregations are designed to search for interesting and/or unusual occurrences of terms in your datasets that can tell much about the hidden properties of your data. This functionality is especially useful for the following use cases:
- Identifying relevant documents for the user queries containing synonyms, acronyms, etc. For example, the significant terms aggregation could suggest documents with "bird flu" when the user searches for H1N1.
- Identifying anomalies and interesting occurrences in your data. For example, by filtering documents based on location, we could identify the most frequent crime types in particular areas.
- Identifying the most significant properties of a group of subjects using the significant terms aggregation on integer fields like height, weight, income, etc.
It should be noted that both significant terms and significant text aggregations perform complex statistical computations on documents retrieved by the direct query (foreground set) and all other documents in your index (background set). Therefore, both aggregations are computationally intensive and should be properly configured to work fast. However, once you master them with the help of this tutorial, you'll acquire a powerful tool for building very useful features in your applications and getting useful insights from your datasets. Let's get started!
-
Comprehensive Guide to Bucket Aggregations in Elasticsearch: Part I
Bucket aggregations in Elasticsearch create buckets or sets of documents based on certain criteria. Depending on the aggregation type, you can create filtering buckets, that is, buckets representing different value ranges and intervals for numeric values, dates, IP ranges, and more.
Although bucket aggregations do not calculate metrics, they can hold metrics sub-aggregations that can calculate metrics for each bucket generated by the bucket aggregation. This makes bucket aggregations very useful for the granular representation and analysis of your Elasticsearch indices. In this article, we'll focus on such bucket aggregations as histogram, range, filters, and terms. Let's get started!
Not yet enjoying the benefits of a hosted ELK-stack enterprise search on Qbox? Discover how easy it is to manage and scale your Elasticsearch environment.