DBMS > Amazon DocumentDB vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. OpenSearch vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Globally distributed, horizontally scalable, multi-model database service

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Vector DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

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

Website

aws.amazon.com/documentdb

firebase.google.com/products/firestore

azure.microsoft.com/services/cosmos-db

github.com/opensearch-project
opensearch.org

yaacomo.com

Technical documentation

aws.amazon.com/documentdb/resources

firebase.google.com/docs/firestore

learn.microsoft.com/azure/cosmos-db

opensearch.org/docs/latest

Developer

Google

Microsoft

Amazon Web Services

Q2WEB GmbH

Initial release

2019

2017

2014

2021

2009

Current release

2.5.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

Android
Linux
Windows

Data scheme

schema-free

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

yes

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 properties auto-indexed by default

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

Java API
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

yes

Triggers

yes, with Cloud Functions

JavaScript

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication

yes

Implicit feature of the cloud service

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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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...
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Licensing and pricing models

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