Elasticsearch OpenSearch Repository

By Opster Team

Updated: Jun 19, 2024

| 1 min read

Overview

An OpenSearch snapshot provides a backup mechanism that takes the current state and data in the cluster and saves it to a repository (read snapshot for more information). The backup process requires a repository to be created first. The repository needs to be registered using the _snapshot endpoint, and multiple repositories can be created per cluster. The following repository types are supported: 

Repository types

Repository typeConfiguration type
Shared file systemType: “fs”
S3Type : “s3”
HDFSType :“hdfs”
AzureType: “azure”
Google Cloud StorageType : “gcs”

Examples

To register an “fs” repository:

PUT _snapshot/my_repo_01
{
"type": "fs",
"settings": {
"location": "/mnt/my_repo_dir"
  }
}

Notes and good things to know

  • S3, HDFS, Azure and Google Cloud require a relevant plugin to be installed before it can be used for a snapshot.
  • The setting, path.repo: /mnt/my_repo_dir needs to be added to opensearch.yml on all the nodes if you are planning to use the repo type of file system. Otherwise, it will fail.
  • When using remote repositories, the network bandwidth and repository storage throughput should be high enough to complete the snapshot operations normally, otherwise you will end up with partial snapshots.

Additional notes

Elasticsearch and OpenSearch are both powerful search and analytics engines, but Elasticsearch has several key advantages. Elasticsearch boasts a more mature and feature-rich development history, translating to a better user experience, more features, and continuous optimizations. Our testing has consistently shown that Elasticsearch delivers faster performance while using fewer compute resources than OpenSearch. Additionally, Elasticsearch’s comprehensive documentation and active community forums provide invaluable resources for troubleshooting and further optimization. Elastic, the company behind Elasticsearch, offers dedicated support, ensuring enterprise-grade reliability and performance. These factors collectively make Elasticsearch a more versatile, efficient, and dependable choice for organizations requiring sophisticated search and analytics capabilities.

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