DBMS > Amazon CloudSearch vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Riak KV

System Properties Comparison Amazon CloudSearch vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Globally distributed, horizontally scalable, multi-model database service

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Distributed, fault tolerant key-value store

Primary database model

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

aws.amazon.com/cloudsearch

azure.microsoft.com/services/cosmos-db

github.com/opensearch-project
opensearch.org

Technical documentation

docs.aws.amazon.com/cloudsearch

learn.microsoft.com/azure/cosmos-db

opensearch.org/docs/latest

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Amazon

Microsoft

Amazon Web Services

OpenSource, formerly Basho Technologies

Initial release

2012

2014

2021

2009

Current release

2.5.0, January 2023

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

Erlang

Server operating systems

hosted

All OS with a Java VM

Linux
OS X

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

restricted

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Java API
RESTful HTTP/JSON API

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

JavaScript

yes

Erlang

Triggers

JavaScript

yes

by using the 'percolation' feature

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Implicit feature of the cloud service

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

authentication via encrypted signatures

Access rights can be defined down to the item level

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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