DBMS > Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. openGemini vs. RethinkDB

System Properties Comparison Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage vs. openGemini vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

www.opengemini.org
github.com/openGemini

rethinkdb.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.opengemini.org/guide

rethinkdb.com/docs

Developer

Microsoft

Huawei and openGemini community

The Linux Foundation

since July 2017

Initial release

2014

2012

2022

2009

Current release

1.1, July 2023

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

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.

Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

Integer, Float, Boolean, String

yes

string, binary, float, bool, date, geometry

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

HTTP REST

Supported programming languages

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

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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 can be defined down to the item level

Access rights based on private key authentication or shared access signatures

Administrators and common users accounts

yes

users and table-level permissions

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