OpenSearch Data Architecture

With cold storage, OpenSearch provides an advanced & efficient storage solution that complements the existing UltraWarm feature. To use...

Elasticsearch ILM (Index Lifecycle Management) & OpenSearch ISM (Index State Management) have the same goal, but their execution differs...

Follow these steps to configure all OpenSearch node role types (master, data, coordinating, ingest, machine learning, remote eligible...

Mappings are the core element of index creation in OpenSearch. Defining them correctly can improve performance. Mapping types include...

Ingest pipelines sit within the OpenSearch node and will perform a set of alterations on your data that you...

The join data type field allows users to establish parent-child relationships between documents in OpenSearch. To use join, you need to...

OpenSearch has many methods for defining relationships between documents, such as nested documents. An OpenSearch nested query...

OpenSearch object types can be used to define relationships between documents. Here's how to use the object field type for that purpose.

When you have too many shards in your OpenSearch cluster, there are a few steps you can take in order to reduce the number of shards...

OpenSearch index templates allow us to create indices with user defined configuration. An index can pull the configuration from these...

Nested is a special object type that is indexed as a separate document. To demonstrate the use of OpenSearch nested fields VS. object...

Elasticsearch & OpenSearch offer ways to save costs by putting older data into cheaper machines. OpenSearch uses UltraWarm and...

This guide will go over the OpenSearch Cross Cluster Search (CCS) & Cross Cluster Replication (CCR) features, how to configure CCR and more.

In this article, we will delve into the different data types supported by OpenSearch and how to use them effectively.

The 2 methods in OpenSsearch to calculate the storage size of specific fields in an index are: creating dedicated indices & using the Luke....

Terms aggregations rely on an internal data structure known as global ordinals. The eager_global_ordinals parameter is used to...

The new match_only_text feature in OpenSearch can save up to 10% of disk space on logging datasets. This field type will set a flat...

Remote-backed storage is an experimental OpenSearch feature. Here's how to enable it, recover data from remote repositories & its limitations.

OpenSearch searchable snapshots allows to search snapshots in remote repositories without pre-downloading all index data to disks. To use...

The OpenSearch segment replication feature copies segments directly to the replica nodes disk after refresh. The architecture design...

There are various methods for retrieving fields in OpenSearch, including: _source, stored_fields, fields & docvalue_fields. To retrieve...

By using the Split Index API in OpenSearch, an existing index can be split to create a new index with extra primary shards. To do this...

The text analysis process in OpenSearch is tasked with two functions: tokenization & normalization and is carried out by employing analyzers.

A tokenizer decides how OpenSearch will take a set of words and divide it into separated terms called “tokens”. To work with synonyms...

OpenSearch transforms allow users to generate new indices based on existing data aggregations. Here's to create index transforms.

OpenSearch offers an easy way to configure a hot-warm architecture under specific conditions. To set up a hot-warm architecture for ISM...

Here are the similarities and differences between Elasticsearch Snapshot Lifecycle Management (SLM) and OpenSearch Snapshot Management (SM).

There are at least three use cases where you should consider using transforms instead of aggregations in OpenSearch. First, when the...