DBMS > eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. RisingWave

System Properties Comparison eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. RisingWave

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Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Globally distributed, horizontally scalable, multi-model database service

Multi-model DBMS (Document, Graph, Key/Value)

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

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

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Website

www.mcobject.com

azure.microsoft.com/services/cosmos-db

orientdb.org

www.risingwave.com/database

Technical documentation

www.mcobject.com/docs/extremedb.htm

learn.microsoft.com/azure/cosmos-db

www.orientdb.com/docs/last/index.html

docs.risingwave.com/docs/current/intro

Developer

McObject

Microsoft

OrientDB LTD; CallidusCloud; SAP

RisingWave Labs

Initial release

2001

2014

2010

2022

Current release

8.2, 2021

3.2.29, March 2024

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

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 and C++

Java

Rust

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

All OS with a Java JDK (>= JDK 6)

Docker
Linux
macOS

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Standard SQL-types and JSON

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.

support of XML interfaces available

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

SQL-like query language, no joins

yes

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

JDBC
PostgreSQL wire protocol

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

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

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

Java, Javascript

UDFs in Python or Java

Triggers

yes

by defining events

JavaScript

Hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Implicit feature of the cloud service

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

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

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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 can be defined down to the item level

Access rights for users and roles; record level security configurable

Users and Roles

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