DBMS > Microsoft Azure Cosmos DB vs. openGemini vs. Oracle Coherence vs. Riak KV vs. TerminusDB

System Properties Comparison Microsoft Azure Cosmos DB vs. openGemini vs. Oracle Coherence vs. Riak KV vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

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

Oracles in-memory data grid solution

Distributed, fault tolerant key-value store

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Key-value store

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

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

azure.microsoft.com/services/cosmos-db

www.opengemini.org
github.com/openGemini

www.oracle.com/java/coherence

terminusdb.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.opengemini.org/guide

docs.oracle.com/en/middleware/standalone/coherence

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

terminusdb.github.io/terminusdb/#

Developer

Microsoft

Huawei and openGemini community

Oracle

OpenSource, formerly Basho Technologies

DataChemist Ltd.

Initial release

2014

2022

2007

2009

2018

Current release

1.1, July 2023

14.1, August 2023

3.2.0, December 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache version 2, commercial enterprise edition

Open Source

GPL V3

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

Java

Erlang

Prolog, Rust

Server operating systems

hosted

Linux
Windows

All OS with a Java VM

Linux
OS X

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

Integer, Float, Boolean, String

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

restricted

SQL

Support of SQL

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

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

HTTP REST

JCache
JPA
RESTful HTTP API

HTTP API
Native Erlang Interface

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

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

.Net
C++
Java

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

JavaScript
Python

Server-side scripts

Stored procedures

JavaScript

Erlang

yes

Triggers

JavaScript

yes

Live Events

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

yes, with selectable consistency level

selectable replication factor

Journaling Streams

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
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

in-memory journaling

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

Administrators and common users accounts

authentification to access the cache via certificates or http basic authentication

yes, using Riak Security

Role-based access control

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