DBMS > Microsoft Azure SQL Database vs. NSDb vs. OrientDB vs. OrigoDB vs. VoltDB

System Properties Comparison Microsoft Azure SQL Database vs. NSDb vs. OrientDB vs. OrigoDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering with high compatibility to Microsoft SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

A fully ACID in-memory object graph database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

azure.microsoft.com/en-us/products/azure-sql/database

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

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

origodb.com/docs

docs.voltdb.com

Developer

Microsoft

OrientDB LTD; CallidusCloud; SAP

Robert Friberg et al

VoltDB Inc.

Initial release

2010

2017

2010

2009

under the name LiveDB

2010

Current release

V12

3.2.29, March 2024

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java, Scala

Java

Java, C++

Server operating systems

hosted

Linux
macOS

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

Linux
Windows

Linux
OS X

for development

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

yes: int, bigint, decimal, string

yes

User defined using .NET types and collections

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.

yes

can be achieved using .NET

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like query language, no joins

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

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

.NET Client API
HTTP API
LINQ

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Java
Scala

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

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Transact SQL

Java, Javascript

yes

Java

Triggers

yes

Hooks

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

depending on model

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Role based authorization

Users and roles with access to stored procedures

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